Division of Immunology and Infectious Disease Biology, INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.
Front Immunol. 2022 Dec 2;13:1034159. doi: 10.3389/fimmu.2022.1034159. eCollection 2022.
Despite numerous efforts to describe COVID-19's immunological landscape, there is still a gap in our understanding of the virus's infections after-effects, especially in the recovered patients. This would be important to understand as we now have huge number of global populations infected by the SARS-CoV-2 as well as variables inclusive of VOCs, reinfections, and vaccination breakthroughs. Furthermore, single-cell transcriptome alone is often insufficient to understand the complex human host immune landscape underlying differential disease severity and clinical outcome.
By combining single-cell multi-omics (Whole Transcriptome Analysis plus Antibody-seq) and machine learning-based analysis, we aim to better understand the functional aspects of cellular and immunological heterogeneity in the COVID-19 positive, recovered and the healthy individuals.
Based on single-cell transcriptome and surface marker study of 163,197 cells (124,726 cells after data QC) from the 33 individuals (healthy=4, COVID-19 positive=16, and COVID-19 recovered=13), we observed a reduced MHC Class-I-mediated antigen presentation and dysregulated MHC Class-II-mediated antigen presentation in the COVID-19 patients, with restoration of the process in the recovered individuals. B-cell maturation process was also impaired in the positive and the recovered individuals. Importantly, we discovered that a subset of the naive T-cells from the healthy individuals were absent from the recovered individuals, suggesting a post-infection inflammatory stage. Both COVID-19 positive patients and the recovered individuals exhibited a CD40-CD40LG-mediated inflammatory response in the monocytes and T-cell subsets. T-cells, NK-cells, and monocyte-mediated elevation of immunological, stress and antiviral responses were also seen in the COVID-19 positive and the recovered individuals, along with an abnormal T-cell activation, inflammatory response, and faster cellular transition of T cell subtypes in the COVID-19 patients. Importantly, above immune findings were used for a Bayesian network model, which significantly revealed and as COVID-19 severity predictors.
In conclusion, COVID-19 recovered individuals exhibited a hyper-activated inflammatory response with the loss of B cell maturation, suggesting an impeded post-infection stage, necessitating further research to delineate the dynamic immune response associated with the COVID-19. To our knowledge this is first multi-omic study trying to understand the differential and dynamic immune response underlying the sample subtypes.
尽管人们已经做出了许多努力来描述 COVID-19 的免疫学特征，但我们对病毒感染后的影响，特别是在已康复的患者中的理解仍然存在差距。这一点很重要，因为我们现在有大量的全球人口感染了 SARS-CoV-2，同时还存在包括 VOC、再感染和疫苗突破在内的各种变量。此外，单细胞转录组本身往往不足以理解导致疾病严重程度和临床结果差异的复杂人类宿主免疫特征。
通过结合单细胞多组学（全转录组分析加抗体测序）和基于机器学习的分析，我们旨在更好地理解 COVID-19 阳性、康复和健康个体中细胞和免疫异质性的功能方面。
基于对来自 33 个人（健康者=4，COVID-19 阳性者=16，COVID-19 康复者=13）的 163197 个细胞（数据 QC 后为 124726 个细胞）的单细胞转录组和表面标记研究，我们观察到 COVID-19 患者的 MHC Ⅰ类介导的抗原呈递减少和 MHC Ⅱ类介导的抗原呈递失调，而在康复者中则恢复了这一过程。B 细胞成熟过程在阳性和康复者中也受到损害。重要的是，我们发现健康个体中的一组幼稚 T 细胞从康复个体中缺失，这表明存在感染后炎症阶段。COVID-19 阳性患者和康复者的单核细胞和 T 细胞亚群中均存在 CD40-CD40LG 介导的炎症反应。COVID-19 阳性患者和康复者的 T 细胞、NK 细胞和单核细胞介导的免疫、应激和抗病毒反应也升高，同时 T 细胞激活、炎症反应和 T 细胞亚型的细胞过渡更快。重要的是，上述免疫发现被用于贝叶斯网络模型，该模型显著揭示和作为 COVID-19 严重程度的预测因子。
总之，COVID-19 康复者表现出过度激活的炎症反应，同时伴有 B 细胞成熟受损，这表明存在感染后阶段受阻，需要进一步研究以阐明与 COVID-19 相关的动态免疫反应。据我们所知，这是首次尝试通过多组学研究来理解样本亚型中不同和动态的免疫反应。
