Resolving the developmental mechanisms of coagulation abnormalities characteristic of SARS-CoV2 based on single-cell transcriptome analysis (preprint)

The COVID-19 outbreak caused by the SARS-CoV-2 virus has developed into a global health emergency. In addition to causing respiratory symptoms following SARS-CoV-2 infection, COVID-19-associated coagulopathy (CAC) is the main cause of death in patients with severe COVID-19. In this study, we performed single-cell sequencing analysis of the right ventricular free wall tissue from healthy donors, patients who died in the hypercoagulable phase of CAC, and patients in the fibrinolytic phase of CAC. Among these, we collected 61,187 cells, which were enriched in 24 immune cell subsets and 13 cardiac-resident cell subsets. We found that in response to SARS-CoV-2 infection, CD9highCCR2high monocyte-derived mo promoted hyperactivation of the immune system and initiated the extrinsic coagulation pathway by activating CXCR-GNB/G-PI3K-AKT. This sequence of events is the main process contributing the development of coagulation disorders subsequent to SARS-CoV-2 infection. In the characteristic coagulation disorder caused by SARS-CoV-2, excessive immune activation is accompanied by an increase in cellular iron content, which in turn promotes oxidative stress and intensifies intercellular competition. This induces cells to alter their metabolic environment, resulting in an increase in sugar uptake, such as that via the glycosaminoglycan synthesis pathway, in CAC coagulation disorders. In addition, high levels of reactive oxygen species generated in response elevated iron levels promote the activation of unsaturated fatty acid metabolic pathways in endothelial cell subgroups, including vascular endothelial cells. This in turn promotes the excessive production of the toxic peroxidation by-product malondialdehyde, which exacerbates both the damage caused to endothelial cells and coagulation disorders.

SARS-CoV-2 nucleocapsid protein dually regulates innate immune responses (preprint)

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global pandemic of COVID-19, may trigger immunosuppression in the early stage and a cytokine storm in the late stage of infection, however, the underlying mechanisms are not well understood. Here we demonstrated that the SARS-CoV-2 nucleocapsid (N) protein dually regulated innate immune responses, i.e., the low-dose N protein suppressed type I interferon (IFN-I) signaling and inflammatory cytokines, whereas high-dose N protein promoted IFN-I signaling and inflammatory cytokines. Mechanistically, the SARS-CoV-2 N protein interacted with the tripartite motif protein 25 (TRIM25), thereby dually regulating the phosphorylation and nuclear translocation of IRF3, STAT1 and STAT2. Additionally, low-dose N protein combined with TRIM25 could suppress retinoic acid-inducible gene I (RIG-I) ubiquitination and activation. Our findings revealed a regulatory mechanism of innate immune responses by the SARS-CoV-2 N protein, which would contribute to understanding the pathogenesis of SARS-CoV-2 and other SARS-like coronaviruses, and development of more effective strategies for controlling COVID-19.

Impaired cellular immunity to SARS-CoV-2 in severe COVID-19 patients (preprint)

The World Health Organization has declared SARS-CoV-2 virus outbreak a world-wide pandemic. Individuals infected by the virus exhibited different degrees of symptoms, the basis of which remains largely unclear. Currently, though convalescent individuals have been shown with both cellular and humoral immune responses, there is very limited understanding on the immune responses, especially adaptive immune responses, in patients with severe COVID-19. Here, we examined 10 blood samples from COVID-19 patients with acute respiratory distress syndrome (ARDS). The majority of them (70%) mounted SARS-CoV-2-specific humoral immunity with production of neutralizing antibodies. However, compared to healthy controls, the percentages and absolute numbers of both NK cells and CD8+ T cells were significantly reduced, accompanied with decreased IFN{gamma} expression in CD4+ T cells in peripheral blood from severe patients. Most notably, we failed in detecting SARS-CoV-2-specific IFN{gamma} production by peripheral blood lymphocytes from these patients. Our work thus indicates that COVID-19 patients with severe symptoms are associated with defective cellular immunity, which not only provides insights on understanding the pathogenesis of COVID-19, but also has implications in developing an effective vaccine to SARS-CoV-2.

Severity detection for the coronavirus disease 2019 (COVID-19) patients using a machine learning model based on the blood and urine tests (preprint)

The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.

Modeling the Control of COVID-19: Impact of Policy Interventions and Meteorological Factors (preprint)

In this paper, we propose a dynamical model to describe the transmission of COVID-19, which is spreading in China and many other countries. To avoid a larger outbreak in the worldwide, Chinese government carried out a series of strong strategies to prevent the situation from deteriorating. Home quarantine is the most important one to prevent the spread of COVID-19. In order to estimate the effect of population quarantine, we divide the population into seven categories for simulation. Based on a Least-Squares procedure and officially published data, the estimation of parameters for the proposed model is given. Numerical simulations show that the proposed model can describe the transmission of COVID-19 accurately, the corresponding prediction of the trend of the disease is given. The home quarantine strategy plays an important role in controlling the disease spread and speeding up the decline of COVID-19. The control reproduction number of most provinces in China are analyzed and discussed adequately. We should pay attention to that, though the epidemic is in decline in China, the disease still has high risk of human-to-human transmission continuously. Once the control strategy is removed, COVID-19 may become a normal epidemic disease just like flu. Further control for the disease is still necessary, we focus on the relationship between the spread rate of the virus and the meteorological conditions. A comprehensive meteorological index is introduced to represent the impact of meteorological factors on both high and low migration groups. As the progress on the new vaccine, we design detail vaccination strategies for COVID-19 in different control phases and show the effectiveness of efficient vaccination. Once the vaccine comes into use, the numerical simulation provide a promptly prospective research.