Alberts Rudi, Chan Sze Chun, Meng Qian-Fang, He Shan, Rao Lang, Liu Xindong, Zhang Yongliang
Department of Microbiology and Immunology, NUSMED Immunology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore.
Immunology Programme, Institute of Life Sciences, National University of Singapore, Singapore117456, Singapore.
Immune Netw. 2022 May 19;22(3):e22. doi: 10.4110/in.2022.22.e22. eCollection 2022 Jun.
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), has spread over the world causing a pandemic which is still ongoing since its emergence in late 2019. A great amount of effort has been devoted to understanding the pathogenesis of COVID-19 with the hope of developing better therapeutic strategies. Transcriptome analysis using technologies such as RNA sequencing became a commonly used approach in study of host immune responses to SARS-CoV-2. Although substantial amount of information can be gathered from transcriptome analysis, different analysis tools used in these studies may lead to conclusions that differ dramatically from each other. Here, we re-analyzed four RNA-sequencing datasets of COVID-19 samples including human bronchoalveolar lavage fluid, nasopharyngeal swabs, lung biopsy and hACE2 transgenic mice using the same standardized method. The results showed that common features of COVID-19 include upregulation of chemokines including , , and , inflammatory cytokine IL-1β and alarmin S100A8/S100A9, which are associated with dysregulated innate immunity marked by abundant neutrophil and mast cell accumulation. Downregulation of chemokine receptor genes that are associated with impaired adaptive immunity such as lymphopenia is another common feather of COVID-19 observed. In addition, a few interferon-stimulated genes but no type I IFN genes were identified to be enriched in COVID-19 samples compared to their respective control in these datasets. These features are in line with results from single-cell RNA sequencing studies in the field. Therefore, our re-analysis of the RNA-seq datasets revealed common features of dysregulated immune responses to SARS-CoV-2 and shed light to the pathogenesis of COVID-19.
2019冠状病毒病(COVID-19)由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起,自2019年末出现以来已在全球传播,引发了一场仍在持续的大流行。人们付出了巨大努力来了解COVID-19的发病机制,希望开发出更好的治疗策略。使用RNA测序等技术进行转录组分析成为研究宿主对SARS-CoV-2免疫反应的常用方法。尽管转录组分析可以收集大量信息,但这些研究中使用的不同分析工具可能会得出截然不同的结论。在这里,我们使用相同的标准化方法重新分析了四个COVID-19样本的RNA测序数据集,包括人类支气管肺泡灌洗液、鼻咽拭子、肺活检和hACE2转基因小鼠。结果表明,COVID-19的共同特征包括趋化因子(包括、和)、炎性细胞因子IL-1β和警报素S100A8/S100A9的上调,这些与以大量中性粒细胞和肥大细胞积聚为特征的先天免疫失调有关。与适应性免疫受损相关的趋化因子受体基因下调,如淋巴细胞减少,是观察到的COVID-19的另一个共同特征。此外,与这些数据集中各自的对照相比,在COVID-19样本中鉴定出一些干扰素刺激基因,但未发现I型干扰素基因富集。这些特征与该领域单细胞RNA测序研究的结果一致。因此,我们对RNA-seq数据集的重新分析揭示了对SARS-CoV-2免疫反应失调的共同特征,并为COVID-19的发病机制提供了线索。