Intracellular Life Cycle Kinetics of SARS-CoV-2 Predicted Using Mathematical Modelling.
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ABSTRACT:
SUBMITTER: Grebennikov D
PROVIDER: S-EPMC8473439 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:When a virus spreads, it may mutate into, e.g., vaccine resistant or fast spreading lineages, as was the case for the Danish Cluster-5 mink variant (belonging to the B.1.1.298 lineage), the British B.1.1.7 lineage, and the South African B.1.351 lineage of the SARS-CoV-2 virus. A way to handle such spreads is through a containment strategy, where the population in the affected area is isolated until the spread has been stopped. Under such circumstances, it is important to monitor whether the mutated virus is extinct via massive testing for the virus sub-type. If successful, the strategy will lead to lower and lower numbers of the sub-type, and it will eventually die out. An important question is, for how long time one should wait to be sure the sub-type is extinct? We use a hidden Markov model for infection spread and an approximation of a two stage sampling scheme to infer the probability of extinction. The potential of the method is illustrated via a simulation study. Finally, the model is used to assess the Danish containment strategy when SARS-CoV-2 spread from mink to man during the summer of 2020, including the Cluster-5 sub-type. In order to avoid further spread and mink being a large animal virus reservoir, this situation led to the isolation of seven municipalities in the Northern part of the country, the culling of the entire Danish 17 million large mink population, and a bill to interim ban Danish mink production until the end of 2021.
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the global pandemic of COVID-19, and no effective antiviral agents and vaccines are available. SARS-CoV-2 is classified as a biosafety level-3 (BLS-3) agent, impeding the basic research into its biology and the development of effective antivirals. Here, we described a safe cell culture system for production of transcription and replication-competent, biologically contained SARS-CoV-2 virus like particles (trVLP) that express a reporter gene (GFP) replacing viral nucleocapsid gene, which is required for viral genome packaging and virion assembly (SARS-CoV-2-GFP/N trVLP). The complete viral life cycle can be exclusively achieved and confined in the cells expressing SARS-CoV or SARS-CoV-2 N proteins in trans, but not MERS-CoV N. Additionally, genetic recombination of N supplied in trans into viral genome was not detected, as evidenced by sequence analysis after one-month serial passages in N-expressing Caco-2 cells. Moreover, Intein-mediated protein trans-splicing approach was utilized to split the viral N gene into two independent vectors, and the ligated viral N protein could function in trans to recapitulate entire viral life cycle, further securing the biosafety of this cell culture model. To prove the suitability of this system in antivirals discovery, we developed a 96-well format high throughput screening to identify salinomycin, monensin sodium and lycorine chloride exhibiting potent antiviral activities against SARS-CoV-2 infection. Collectively, we propose that this cell culture system based on Intein-N genetic complementation to produce SARS-CoV-2 trVLP provides a safe means to dissect the virus life cycle, and thus accelerate our understanding of virus biology, as well as for more applied uses such as the screening and development of novel antivirals, and thus represent powerful tools for SARS-CoV-2 study.
2020-12-03 | GSE162629 | GEO
Project description:ObjectivesTo exploit the features of digital PCR for implementing SARS-CoV-2 observational studies by reliably including the viral load factor expressed as copies/μL.MethodsA small cohort of 51 Covid-19 positive samples was assessed by both RT-qPCR and digital PCR assays. A linear regression model was built using a training subset, and its accuracy was assessed in the remaining evaluation subset. The model was then used to convert the stored cycle threshold values of a large dataset of 6208 diagnostic samples into copies/μL of SARS-CoV-2. The calculated viral load was used for a single cohort retrospective study. Finally, the cohort was randomly divided into a training set (n = 3095) and an evaluation set (n = 3113) to establish a logistic regression model for predicting case-fatality and to assess its accuracy.ResultsThe model for converting the Ct values into copies/μL was suitably accurate. The calculated viral load over time in the cohort of Covid-19 positive samples showed very low viral loads during the summer inter-epidemic waves in Italy. The calculated viral load along with gender and age allowed building a predictive model of case-fatality probability which showed high specificity (99.0%) and low sensitivity (21.7%) at the optimal threshold which varied by modifying the threshold (i.e. 75% sensitivity and 83.7% specificity). Alternative models including categorised cVL or raw cycle thresholds obtained by the same diagnostic method also gave the same performance.ConclusionThe modelling of the cycle threshold values using digital PCR had the potential of fostering studies addressing issues regarding Sars-CoV-2; furthermore, it may allow setting up predictive tools capable of early identifying those patients at high risk of case-fatality already at diagnosis, irrespective of the diagnostic RT-qPCR platform in use. Depending upon the epidemiological situation, public health authority policies/aims, the resources available and the thresholds used, adequate sensitivity could be achieved with acceptable low specificity.
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of individuals worldwide, causing a severe global pandemic. Mice models are wildly used to investigate viral infection pathology, antiviral drugs, and vaccine development. However, since wild-type mice do not express human angiotensin-converting enzyme 2 (hACE2), which mediates SARS-CoV-2 entry into human cells, they are not susceptible to infection with SARS-CoV-2 and are not suitable to simulate symptomatic COVID-19 disease. HACE2 transgenic mice could provide an efficient model, but they are expensive, not always readily available and practically restricted to specific strain(s). Since additional models are needed to study the disease at varying genetic and immune backgrounds, there is a dearth of mouse models for SARS-CoV-2 infection. Here we report the application of lentiviral vectors to generate hACE2 expression in mouse lung epithelial cells (LET1) as well as in interferon receptor knock-out (IFNAR1-/-) mice. Lenti-hACE2 transduction supported SARS-CoV-2 replication both in vitro and in vivo, simulating mild acute lung disease1. Gene expression analysis revealed two modes of immune responses to SARS-CoV-2 infection: one in response to the exposure of mouse lungs to SARS-CoV-2 particles in the absence of productive viral replication, and the second in response to a productive infection. This approach expands our knowledge on the role of type-1 interferon signaling in COVID-19 disease, and can be further implemented for a range of COVID-19 studies and drug development.
2021-12-07 | GSE186167 | GEO
Project description:BackgroundEngland's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.MethodsThis mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.FindingsThe roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness.InterpretationOur findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures.FundingNational Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.
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Project description:A newly emerged coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), belongs to the β-coronavirus family and shows high similarities with SARS-CoV. On March 11, 2020, the World Health Organization (WHO) declared SARS-CoV-2 a global pandemic, and the disease was named the coronavirus disease 2019 (COVID-19). The ongoing COVID-19 pandemic has caused over 46 million infections and over one million deaths worldwide, and the numbers are still increasing. Efficacious antiviral agents are urgently needed to combat this virus. The life cycle of SARS-CoV-2 mainly includes the viral attachment, membrane fusion, genomic replication, assembly and budding of virions. Accordingly, drug development against SARS-CoV-2 currently focuses on blocking spike protein binding to ACE2, inhibiting viral membrane fusion with host cells, and preventing the viral replication by targeting 3C-like protease, papain-like protease, RNA-dependent RNA polymerase as well as some host-cell proteins. In this review, the advances of drug development in these three major areas are elaborated.
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the global pandemic of COVID-19. SARS-CoV-2 is classified as a biosafety level-3 (BSL-3) agent, impeding the basic research into its biology and the development of effective antivirals. Here, we developed a biosafety level-2 (BSL-2) cell culture system for production of transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP). This trVLP expresses a reporter gene (GFP) replacing viral nucleocapsid gene (N), which is required for viral genome packaging and virion assembly (SARS-CoV-2 GFP/ΔN trVLP). The complete viral life cycle can be achieved and exclusively confined in the cells ectopically expressing SARS-CoV or SARS-CoV-2 N proteins, but not MERS-CoV N. Genetic recombination of N supplied in trans into viral genome was not detected, as evidenced by sequence analysis after one-month serial passages in the N-expressing cells. Moreover, intein-mediated protein trans-splicing approach was utilized to split the viral N gene into two independent vectors, and the ligated viral N protein could function in trans to recapitulate entire viral life cycle, further securing the biosafety of this cell culture model. Based on this BSL-2 SARS-CoV-2 cell culture model, we developed a 96-well format high throughput screening for antivirals discovery. We identified salinomycin, tubeimoside I, monensin sodium, lycorine chloride and nigericin sodium as potent antivirals against SARS-CoV-2 infection. Collectively, we developed a convenient and efficient SARS-CoV-2 reverse genetics tool to dissect the virus life cycle under a BSL-2 condition. This powerful tool should accelerate our understanding of SARS-CoV-2 biology and its antiviral development.
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Project description: Not available
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