SARS-CoV-2 infection induces beta cell transdifferentiation

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Natural killer cell exhaustion in SARS-CoV-2 infection

At the end of 2019, an outbreak of a severe respiratory disease occurred in Wuhan China, and an increase in cases of unknown pneumonia was alerted. In January 2020, a new coronavirus named SARS-CoV-2 was identified as the cause. The virus spreads primarily through the respiratory tract, and lymphopenia and cytokine storms have been observed in severely ill patients. This suggests the existence of an immune dysregulation as an accompanying event during a serious illness caused by this virus. Natural killer (NK) cells are innate immune responders, critical for virus shedding and immunomodulation. Despite its importance in viral infections, the contribution of NK cells in the fight against SARS-CoV-2 has yet to be deciphered. Different studies in patients with COVID-19 suggest a significant reduction in the number and function of NK cells due to their exhaustion. In this review, we summarize the current understanding of how NK cells respond to SARS-CoV-2 infection.     

SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis

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Receptor-binding domain of SARS-CoV-2 spike protein efficiently inhibits SARS-CoV-2 infection and attachment to mouse lung

COVID-19, caused by a novel coronavirus, SARS-CoV-2, poses a serious global threat. It was first reported in 2019 in China and has now dramatically spread across the world. It is crucial to develop therapeutics to mitigate severe disease and viral spread. The receptor-binding domains (RBDs) in the spike protein of SARS-CoV and MERS-CoV have shown anti-viral activity in previous reports suggesting that this domain has high potential for development as therapeutics. To evaluate the potential antiviral activity of recombinant SARS-CoV-2 RBD proteins, we determined the RBD residues of SARS-CoV-2 using a homology search with RBD of SARS-CoV. For efficient expression and purification, the signal peptide of spike protein was identified and used to generate constructs expressing recombinant RBD proteins. Highly purified RBD protein fused with the Fc domain of human IgG showed potent anti-viral efficacy, which was better than that of a protein fused with a histidine tag. Intranasally pre-administrated RBD protein also inhibited the attachment of SARS-COV-2 to mouse lungs. These findings indicate that RBD protein could be used for the prevention and treatment of SARS-CoV-2 infection.     

新型冠状病毒基因组序列的网络平台与基因分型

新型冠状病毒(SARS-CoV-2)是引起2019新型冠状病毒肺炎(COVID-19)的病原体,目前COVID-19仍在世界范围内大规模流行。随着学者对SARS-CoV-2研究的不断深入,以及各大数据库的序列资源共享,一些学者开发了SARS-CoV-2相关序列分析网络在线平台,并发表了对SARS-CoV-2基因分型、命名的规则。"GISAID"是目前SARS-CoV-2基因组序列共享和储存最大的数据库,"Nextstrain"和"CoV-GLUE"是国际最常用的SARS-CoV-2序列分析平台。目前有四种比较通用的SARS-CoV-2的基因分型方法,在本文中分别简称为:"中国分型法"、"Pangolin分型法"、"GISAID分型法"和"Nextstrain分型法"。这四种分型方法的定义不尽相同,但又有相似之处。本综述对目前SARS-CoV-2在线分析网络平台和不同的基因分型方法进行了较为系统的介绍、对比和总结。     

MUC1-C influences cell survival in lung adenocarcinoma Calu-3 cells after SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces coronavirus disease 2019 (COVID-19) and may increase the risk of adverse outcomes in lung cancer patients. In this study, we investigated the expression and function of mucin 1 (MUC1) after SARS-CoV-2 infection in the lung epithelial cancer cell line Calu-3. MUC1 is a major constituent of the mucus layer in the respiratory tract and contributes to pathogen defense. SARS-CoV-2 infection induced MUC1 C-terminal subunit (MUC1-C) expression in a STAT3 activation-dependent manner. Inhibition of MUC1-C signaling increased apoptosis-related protein levels and reduced proliferation-related protein levels; however, SARS-CoV-2 replication was not affected. Together, these results suggest that increased MUC1-C expression in response to SARS-CoV-2 infection may trigger the growth of lung cancer cells, and COVID-19 may be a risk factor for lung cancer patients.     

Diltiazem inhibits SARS-CoV-2 cell attachment and internalization and decreases the viral infection in mouse lung

The continuous emergence of severe acute respiratory coronavirus 2 (SARS-CoV-2) variants and the increasing number of breakthrough infection cases among vaccinated people support the urgent need for research and development of antiviral drugs. Viral entry is an intriguing target for antiviral drug development. We found that diltiazem, a blocker of the L-type calcium channel Ca_v1.2 pore-forming subunit (Ca_v1.2 α_1c) and an FDA-approved drug, inhibits the binding and internalization of SARS-CoV-2, and decreases SARS-CoV-2 infection in cells and mouse lung. Ca_v1.2 α_1c interacts with SARS-CoV-2 spike protein and ACE2, and affects the attachment and internalization of SARS-CoV-2. Our finding suggests that diltiazem has potential as a drug against SARS-CoV-2 infection and that Ca_v1.2 α_1c is a promising target for antiviral drug development for COVID-19.     

Genome composition and genetic characterization of SARS-CoV-2

SARS-CoV-2 is a type of Betacoronaviruses responsible for COVID-19 pandemic disease, with more than 1.745 million fatalities globally as of December-2020. Genetically, it is considered the second largest genome of all RNA viruses with a 5′ cap and 3′ poly-A tail. Phylogenetic analyses of coronaviruses reveal that SARS-CoV-2 is genetically closely related to the Bat-SARS Like-Corona virus (Bat-SL-Cov) with 96% whole-genome identity. SARS-CoV-2 genome consists of 15 ORFs coded into 29 proteins. At the 5′ terminal of the genome, we have ORF1ab and ORF1a, which encode the 1ab and 1a polypeptides that are proteolytically cleaved into 16 different nonstructural proteins (NSPs). The 3′ terminal of the genome represents four structural (spike, envelope, matrix, and nucleocapsid) and nine accessory (3a, 3b, 6, 7a, 7b, 8b, 9a, 9b, and orf10) proteins. As the number of COVID-19 patients increases dramatically worldwide, there is an urgent need to find a quick and sensitive diagnostic tool for controlling the outbreak of SARS-CoV-2 in the community. Today, molecular testing methods utilizing viral genetic material (e.g., PCR) represent the crucial diagnostic tool for the SARS-CoV-2 virus despite its low sensitivity in the early stage of viral infection. This review summarizes the genome composition and genetic characterization of the SARS-CoV-2.     

Host metabolism dysregulation and cell tropism identification in human airway and alveolar organoids upon SARS-CoV-2 infection

The coronavirus disease 2019 (COVID-19) pandemic is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),which is spread primary via respiratory droplets and infects the lungs.Currently widely used cell lines and animals are unable to accurately mimic human physiological conditions because of the abnormal status of cell lines (transformed or cancer cells) and species differences between ani-mals and humans.Organoids are stem cell-derived self-organized three-dimensional culture in vitro and model the physiological conditions of natural organs.Here we showed that SARS-CoV-2 infected and extensively replicated in human embryonic stem cells (hESCs)-derived lung organoids,including airway and alveolar organoids which covered the complete infection and spread route for SARS-CoV-2 within lungs.The infected cells were ciliated,club,and alveolar type 2 (AT2) cells,which were sequentially located from the proximal to the distal airway and terminal alveoli,respectively.Addi-tionally,RNA-seq revealed early cell response to virus infection including an unexpected downregulation of the metabolic processes,especially lipid metabolism,in addition to the well-known upregulation of immune response.Further,Remdesivir and a human neutralizing antibody potently inhibited SARS-CoV-2 replication in lung organoids.Therefore,human lung organoids can serve as a pathophysiological model to investigate the underlying mechanism of SARS-CoV-2 infection and to discover and test therapeutic drugs for COVID-19.     

Data-driven multi-scale mathematical modeling of SARS-CoV-2 infection reveals heterogeneity among COVID-19 patients

Patients with coronavirus disease 2019 (COVID-19) often exhibit diverse disease progressions associated with various infectious ability, symptoms, and clinical treatments. To systematically and thoroughly understand the heterogeneous progression of COVID-19, we developed a multi-scale computational model to quantitatively understand the heterogeneous progression of COVID-19 patients infected with severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2). The model consists of intracellular viral dynamics, multicellular infection process, and immune responses, and was formulated using a combination of differential equations and stochastic modeling. By integrating multi-source clinical data with model analysis, we quantified individual heterogeneity using two indexes, i.e., the ratio of infected cells and incubation period. Specifically, our simulations revealed that increasing the host antiviral state or virus induced type I interferon (IFN) production rate can prolong the incubation period and postpone the transition from asymptomatic to symptomatic outcomes. We further identified the threshold dynamics of T cell exhaustion in the transition between mild-moderate and severe symptoms, and that patients with severe symptoms exhibited a lack of naïve T cells at a late stage. In addition, we quantified the efficacy of treating COVID-19 patients and investigated the effects of various therapeutic strategies. Simulations results suggested that single antiviral therapy is sufficient for moderate patients, while combination therapies and prevention of T cell exhaustion are needed for severe patients. These results highlight the critical roles of IFN and T cell responses in regulating the stage transition during COVID-19 progression. Our study reveals a quantitative relationship underpinning the heterogeneity of transition stage during COVID-19 progression and can provide a potential guidance for personalized therapy in COVID-19 patients.     

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.     

Global analysis of protein-RNA interactions in SARS-CoV-2-infected cells reveals key regulators of infection

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Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs

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Genome sequence analysis of nsp15 from SARS-CoV-2

SARS-CoV-2 (Severe Acute Respiratory Syndrome), a causative agent of COVID-19 disease created a pandemic situation worldwide. Nsp15 is a uridine specific endoribonuclease encoded by the genome of SARS-CoV-2. It plays important role in processing viral RNA and, thus evades the host immune system. Therefore, it is of interest to identify mutants of nsp15 amongst Asian SARS-CoV-2 isolates, where a total of 1795 mutations, from 7793 sequences of Asia submitted till 31st January 2022, amongst which A231V, H234Y, K109N, K259R and S261A mutations were found frequent. Hence, we report data on the predicted secondary structure of wild type form followed by hydropathy plot, physiochemical properties, Ramachandran plot, B-cell epitopes prediction and protein modeling of wild type and mutant of nsp15 protein. Data shows that nsp15 of SARS-CoV-2 is a pontential candidate for the development of vaccine to control the infections of SARS-CoV-2.     

新型冠状病毒基因组G-四链体结构的初步研究

21世纪以来,冠状病毒频频引起危害人类健康的重要传染病,其中包括2003年严重急性呼吸综合征冠状病毒(SARS-CoV)、2012年中东呼吸综合征冠状病毒(MERS-CoV)和新型冠状病毒(SARS-CoV-2),目前对这些病毒引发的疾病并无特效的治疗药物。G-四链体(G-quadruplex,G4)是在DNA或RNA的鸟嘌呤富集区形成的非典型二级结构,可存在于人类和病毒基因组中,G-四链体的不同位置对病毒复制和感染等过程发挥重要调控作用。本研究针对七种与人类疾病相关的冠状病毒以及与SARS-CoV-2同源性较高的三种蝙蝠相关病毒,通过全基因组序列分析潜在四链体形成序列(Potential quadruplex-forming sequences,PQS),结果发现,十种病毒中均存在一定数量的PQS基序,同时对SARS-CoV-2 G-四链体存在位置及形成潜力进行评估,并分析了不同变异株间G-四链体基序的保守性。本研究对SARS-CoV-2基因组中G-四链体进行初步预测与探讨,旨在为COVID-19治疗提供一种新的药物靶点,使其更好地应用于临床研究。     

Host variations in SARS-CoV-2 infection

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the zoonotic pathogen that causes the “Coronavirus Disease of 2019 (COVID-19)”, and COVID-19 itself is yet to be thoroughly understood. Both the disease as well as the mechanisms by which the host interacts with the SARS-CoV-2 have not been fully enlightened. The epidemiological factors –e.g. age, sex, race-, the polymorphisms of the host proteins, the blood types and individual differences have all been in discussions about affecting the progression and the course of COVID-19 both individually and collectively, as their effects are mostly interwoven. We focused mainly on the effect of polymorphic variants of the host proteins that have been shown to take part in and/or affect the pathogenesis of COVID-19. Additionally, how the procedures of diagnosing and treating COVID-19 are affected by these variants and what possible changes can be implemented are the other questions, which are sought to be answered.     

Dissecting lipid metabolism alterations in SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the COVID-19 pandemic that has infected over a hundred million people globally. There have been more than two million deaths recorded worldwide, with no end in sight until a widespread vaccination will be achieved. Current research has centred on different aspects of the virus interaction with cell surface receptors, but more needs to be done to further understand its mechanism of action in order to develop a targeted therapy and a method to control the spread of the virus. Lipids play a crucial role throughout the viral life cycle, and viruses are known to exploit lipid signalling and synthesis to affect host cell lipidome. Emerging studies using untargeted metabolomic and lipidomic approaches are providing new insight into the host response to COVID-19 infection. Indeed, metabolomic and lipidomic approaches have identified numerous circulating lipids that directly correlate to the severity of the disease, making lipid metabolism a potential therapeutic target. Circulating lipids play a key function in the pathogenesis of the virus and exert an inflammatory response. A better knowledge of lipid metabolism in the host-pathogen interaction will provide valuable insights into viral pathogenesis and to the development of novel therapeutic targets.     

Rapid Acquisition of High-Quality SARS-CoV-2 Genome via Amplicon-Oxford Nanopore Sequencing

Virologica Sinica - Genome sequencing has shown strong capabilities in the initial stages of the COVID-19 pandemic such as pathogen identification and virus preliminary tracing. While the rapid...