SARS-CoV-2,COVID-19 z-bo 2020-12-18 358

　　Introduction: After the virus replicates, the physiological response to the virus infection usually begins at the cellular level. After the virus enters, the infected cells through any of the multiple pattern recognition receptors (PRR) will detect the replication of the virus. These receptors physically bind to different structures shared by different pathogens and act as sentinels for various microorganisms inside and outside the cell. In the case of viral infection, the detection of cell replication is largely mediated by the intracellular PRR family, which perceives the abnormal RNA structure often formed during viral replication. The involvement of virus-specific RNA structures ultimately leads to the oligomerization of these receptors and the activation of downstream transcription factors (especially interferon regulatory factor (IRF) and nuclear factor κB (NF-κB)). The transcriptional activation of IRFs and NF-κB led to the initiation of two conventional antiviral programs. The first is to participate in cellular antiviral defense, which is mediated by transcriptional induction of type I and type III interferons (IFN-I and IFN-III, respectively) and subsequent upregulation of IFN-stimulating genes (ISGs). The second aspect of the antiviral response involves the recruitment and coordination of specific white blood cell subpopulations, which are mainly regulated by the secretion of chemokines. This extensive antiviral response exerted selective pressure on the virus and led to the development of countless virus countermeasures. Therefore, the host's response to the virus is usually inconsistent, and infection can cause varying degrees of morbidity and mortality. The current COVID-19 pandemic is a serious and rapidly developing global health crisis. To better understand the molecular basis of the disease, we tried to characterize the transcriptional response to infection in various model systems, including in vitro tissue culture, in vitro infection of primary cells, and in vivo samples from COVID-19 patients and animals. We chose to characterize the transcription response of SARS-CoV-2 and determine its comparison with common respiratory viruses (including influenza A virus (IAV)). These two respiratory viruses encode a variety of different IFN-I and -III response antagonists. For the closely related SARS-CoV-1, the antagonism of IFN can be attributed to ORF3B, ORF6 and nucleocapsid (N) gene products. Similar to SARS-CoV-1, IAV also encodes IFN-I and -III antagonist nonstructural protein 1 (NS1), which prevents the initial detection of PRR by binding and masking abnormal RNA produced during the infection.

　　Here, we compare the transcriptional response of SARS-CoV-2 with other respiratory viruses to determine the transcriptional features that may form the biological basis of COVID-19. These data indicate that the overall transcriptional induction of SARS-CoV-2 is abnormal. Despite viral replication, the host's response to SARS-CoV-2 failed to initiate a strong IFN-I and -III response, and at the same time induced high levels of chemokines required to recruit effector cells. Because a weakened immune response will allow the virus to continue to replicate, these findings may explain why severe COVID-19 cases are more frequently observed in patients with comorbidities.

　　Result: SARS-CoV-2 transcriptional response relative to other respiratory viruses In order to compare the transcriptional response of SARS-CoV-2 with other respiratory viruses (including MERS-CoV, SARS-CoV-1, human parainfluenza virus 3 (HPIV3), respiratory syncytial virus (RSV) and IAV), we first chose The infection of a variety of respiratory tract cell lines is the research object. To this end, we collected poly(A) RNA from infected cells and performed RNA sequencing (RNA-seq) to estimate viral load. These data indicate that the virus infection level accounts for more than 0.1% to 50% of the total RNA reads. Consistent with the results of other studies, we found that A549 alveolar cells are relatively not allowed to replicate SARS-CoV-2, while Calu-3 is the opposite. It is speculated that the low infection rate in A549 cells is the result of low expression of the viral receptor ACE2. In order to bypass this limitation, we added a vector expressing mCherry or ACE2 to A549 cells. In low MOI infection (MOI, 0.2), the expression of exogenous ACE2 enables SARS-CoV-2 to replicate. Western blot analysis confirmed these RNA-seq data, showing that nucleocapsid (N) is only expressed in ACE2 added cells. In addition, qPCR analysis of these cells showed that in the presence of ACE2, the levels of envelope (E) and non-structural protein 14 (nsp14) were more than 3 orders of magnitude higher than that of normal cells. It is worth noting that despite the sharp increase in viral load, we have not observed the activation of TBK1 (the kinase responsible for the expression of IFN-I and IFN-III), nor the activation of STAT1 and MX1 (genes stimulated by IFN-I). Induce. However, the lack of IFN-I and -III participation in A549 cells expressing ACE2 can be overcome by using a 10-fold virus (MOI, 2).

　　In order to determine whether SARS-CoV-2 is sensitive to IFN-I, we next treated the cells with general-purpose IFNβ and evaluated the virus level at the RNA and protein levels. These data indicate that the addition of IFN-I leads to a significant reduction in virus replication, which is consistent with the results of other studies. We also observed that when IFN-I signaling was blocked by the JAK1 and 2 kinase inhibitor ruxolitinib, although it significantly prevented the induction of ISGs, the peak level of the virus did not increase. On the contrary, ruxolitinib treatment has little induction of cytokines and chemokines, indicating that the high induction of these genes in SARS-CoV-2 infection has nothing to do with IFN-I and -III signaling.

　　In order to determine how these in vitro infections change the host transcription environment, we first performed differential expression analysis and compared the conditions of the infected cells with their respective simulated conditions. These analyses indicate that the transcriptional response in cells that allow SARS-CoV-2 to replicate highly is significantly different from the host response of all other tested viruses. In addition, despite the comparable viral load, SARS-CoV-2 infection in unmodified A549 cells showed a unique response compared to SARS-CoV-1. HPIV3 and RSV form a unique cluster, represented by the high expression of IFNs and ISGs. Interestingly, low-MOI SARS-CoV-2 infected A549 cells (A549-ACE2) expressing ACE2 did not show significant IFN-I or IFN-III expression, but showed a moderate level of ISGs subgroups and unique Characteristics of pro-inflammatory cytokines. In A549-ACE2 and Calu-3 cells, SARS-CoV-2 high MOI infection and more than 6000 other differentially expressed genes also have this feature. In addition, despite the significant differences in virus replication, high MOI infection in these cells also resulted in high induction of IFN and ISG in HPIV3 and RSV. The difference between the level of viral replication and the level of IFN production/signaling indicates that although SARS-CoV-2 can bind to the IFN-I and IFN-III systems, antagonists that are ineffective under high MOI conditions can prevent this response .

　　SARS-CoV-2 induces limited IFN-I and III responses in primary cells: In view of the different results of the in vitro cell culture system, we next tried to determine the response of normal human bronchial epithelial cells (NHBE) to SARS-CoV-2 infection, instead of using IFN-I alone or infecting wild-type IAV or lacking antiviral antagonists The mutant IAV (IAVΔNS1). Treatment of NHBE cells with IFN-I can significantly induce 381 genes, most of which are also differentially expressed in IAVΔNS1 infection, which together outlines the strong innate immune response in these cells. Although the level of replication is different, the transcriptional responses of SARS-CoV-2 and WT IAV are similar in quantity, but different in nature. There are only 8 significant inducible genes in common, including interleukin-6 (IL-6), IRF9, ICAM1 and tumor necrosis factor (TNF). For IAV, this weakening of the antiviral response is mediated by the expression of NS1, because IAVΔNS1 infection induces IFNB and IFNL1-3. Despite the complete lack of IFN expression, the response of NHBE cells to SARS-CoV-2 still causes strong chemotaxis and inflammation, which are manifested as CCL20, CXCL1, IL-1B, IL-6, CXCL3, CXCL5, CXCL6, CXCL2, CXCL16 And TNF expression. In addition to the moderate IFN-I response, SARS-CoV-2 in NHBE cells also triggered some unique pathways, including the response to IFN-II and the significant enrichment of chemokine signals.

　　In order to determine whether the limited response to SARS-CoV-2 currently observed is a by-product of cell culture, we next conducted a longitudinal study in animals. For this reason, we chose to carry out SARS-CoV-2 infection in ferrets, because this is a suitable animal model. Ferrets were infected with SARS-CoV-2 or influenza A/California/04/2009 through the nose, and a small amount of cells were collected from the upper respiratory tract through nasal irrigation. RNA sequence analysis was performed on these cells, allowing us to quantify viral load. The data read from the nasal irrigation fluid 1 day after infection showed that the level of virus replication was low, accounting for 0.006% of the total read volume. Three days after infection, the virus replication level reached a peak at 1.2% of the total readings, and then fell to 0.05% of the total readings on the 7th day, and the virus was completely eliminated on the 14th day. In contrast, on day 7, sublethal infections of IAV accounted for<0.03% of the total readings of the same sample type. The presence of the nasal cavity virus further indicates that these ferrets have the potential to spread the virus, which is consistent with the findings of others.

　　In order to characterize the response to SARS-CoV-2 over time, the upper respiratory tract cell population was compared with a simulated ferret. On the first day after infection, we observed very small differences in transcription related to the amount of virus detected. By day 3, we observed the onset of the cytokine response labeled with CCL8 and CXCL9, which was consistent with what was observed in cell culture. By day 7, despite the decline in virus levels, the cytokine response continued to expand, including CCL2, CCL8, and CXCL9. In addition, we noticed that the mixed leukocyte infiltration in CD163, CD226, CCR5, CCR6, CXCR1, CXCR2 and CXCR7 were significantly upregulated. Overall, the intensity of this transcriptional response in the upper respiratory tract is significantly lower compared to similar IAV infections. However, although IAV induced more genes, SARS-CoV-2 produced a unique gene signature, enriching genes for cell death and white blood cell activation, including transcripts such as IL1A and CXCL8. In contrast, the transcriptional footprint of IAV related to cellular antiviral response is significantly larger than that of SARS-CoV-2, including IFN marker genes MX1, ISG20, OASL and Tetherin. By day 14, we did not detect SARS-CoV-2, and the observed cytokines returned to baseline, but IL-6 and IL1RN or IL1RA were still elevated, similar to the results observed by MERS.

　　Finally, in order to study how the host's response to SARS-CoV-2 and IAV affects the respiratory tract, we then performed a parallel infection and checked the trachea on the third day. In both infections, we observed that the virus level was very low, but the transcription response was strong. The gene enrichment analysis of differentially expressed transcription involves two characteristic groups of immune cells. The first feature group includes common markers of monocytes and lymphocytes, and the induction of these genes is comparable between SARS-CoV-2 and IAV. Interestingly, the unique genetic characteristics of SARS-CoV-2 infected trachea are consistent with the genetic characteristics of hematopoietic progenitor cells, indicating that infection may induce hematopoiesis.

　　COVID-19 patients present low IFN-I and -III and high chemokine characteristics:

　　After describing the characteristics of SARS-CoV-2 infection in ferrets, we next tried to link these results with natural human infection. To this end, we first compared post-mortem lung samples from COVID-19-positive patients with healthy lung tissue from uninfected people. The transcription profile analysis of these samples were all from men over 60 years old (n=2 per group), showing about 2,000 differentially expressed genes. Genes that have a significant response to SARS-CoV-2 include a subgroup of ISGs, and RNA-seq or semi-quantitative PCR did not detect IFN-I or IFN-III. In addition to genes for innate antiviral immunity, SARS-CoV-2 also induces increased levels of chemokines, including CCL2, CCL8 and CCL11. Although the number of patients analyzed is limited, these data confirm our findings in NHBE and ferrets. Next, we hope to further validate our findings in more patient populations by directly detecting circulating cytokines induced by SARS-CoV-2 infection. To this end, we obtained serum from two groups of people at the Kaiser Santa Clara testing facility. Nasopharyngeal swabs tested positive for SARS-CoV-2 in these two groups, or were admitted to hospital for non-COVID-19 related respiratory problems (24 cases in each group). In the initial analysis, these serum samples were always negative for IFNβ and IFNλ. In addition, analysis of cytokines and chemokines in a single serum sample showed that COVID-19 patients have increased systemic inflammation, which is characterized by a significant increase in circulating levels of IL-6, IL1RA, CCL2, CCL8, CXCL2, CXCL8, CXCL9, and CXCL16. high. CXCL9 and CXCL16 (respectively are chemokines for T cells or natural killer (NK) cells), CCL8 and CCL2 (recruit monocytes and/or macrophages), and CXCL8 (typical neutrophil chemokines) The significant increase indicates that the presence of these cells may be the main driver of the characteristic pathology observed in COVID-19 patients. Although this sample size does not necessarily represent all patients infected with COVID-19, our data is consistent with what we have observed using other model systems. Additional sampling is needed to verify these findings. "To sum up, the data provided here show that the host's response to SARS-CoV-2 is unbalanced in terms of controlling viral replication and the activation of adaptive immune responses. In view of this dynamic, the treatment of COVID-19 has a smaller relationship with IFN response and a greater relationship with controlling inflammation. Because our data shows that there are a large number of chemokines and ILs elevated in COVID-19 patients,Future work should focus on FDA-approved drugs, which can be quickly applied and have immunomodulatory properties.