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Engineering SARS-CoV-2 using a reverse genetic system.

ABSTRACT: Reverse genetic systems are a critical tool for studying viruses and identifying countermeasures. In response to the ongoing COVID-19 pandemic, we recently developed an infectious complementary DNA (cDNA) clone for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The reverse genetic system can be used to rapidly engineer viruses with desired mutations to study the virus in vitro and in vivo. Viruses can also be designed for live-attenuated vaccine development and engineered with reporter genes to facilitate serodiagnosis, vaccine evaluation and antiviral screening. Thus, the reverse genetic system of SARS-CoV-2 will be widely used for both basic and translational research. However, due to the large size of the coronavirus genome (~30,000 nucleotides long) and several toxic genomic elements, manipulation of the reverse genetic system of SARS-COV-2 is not a trivial task and requires sophisticated methods. Here, we describe the technical details of how to engineer recombinant SARS-CoV-2. Overall, the process includes six steps: (i) prepare seven plasmids containing SARS-CoV-2 cDNA fragment(s), (ii) prepare high-quality DNA fragments through restriction enzyme digestion of the seven plasmids, (iii) assemble the seven cDNA fragments into a genome-length cDNA, (iv) in vitro transcribe RNA from the genome-length cDNA, (iv) electroporate the genome-length RNA into cells to recover recombinant viruses and (vi) characterize the rescued viruses. This protocol will enable researchers from different research backgrounds to master the use of the reverse genetic system and, consequently, accelerate COVID-19 research.

SUBMITTER: Xie X

PROVIDER: S-EPMC8168523 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundIn any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous?or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only?instantaneous interactions, and are unable to infer time-delayed interactions.ResultsIn this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization.ConclusionThe four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in Escherichia coli?show a significant improvement compared with other state-of-the-art approaches for GRN modeling.

Project description:BackgroundThe COVID-19 agent, SARS-CoV-2, is conspecific with SARS-CoV, the causal agent of the severe acute respiratory syndrome epidemic in 2002-03. Although the viruses share a completely homologous repertoire of proteins and use the same cellular entry receptor, their transmission efficiencies and pathogenetic traits differ. We aimed to compare interferon antagonism by SARS-CoV and SARS-CoV-2.MethodsFor this functional study, we infected Vero E6 and Calu-3 cells with strains of SARS-CoV and SARS-CoV-2. We studied differences in cell line-specific replication (Vero E6 vs Calu-3 cells) and analysed these differences in relation to TMPRSS2-dependent cell entry based on inhibition with the drug camostat mesilate. We evaluated viral sensitivity towards type I interferon treatment and assessed cytokine induction and type I interferon signalling in the host cells by RT-PCR and analysis of transcription factor activation and nuclear translocation. Based on reverse genetic engineering of SARS-CoV, we investigated the contribution of open reading frame 6 (ORF6) to the observed phenotypic differences in interferon signalling, because ORF6 encodes an interferon signalling antagonist. We did a luciferase-based interferon-stimulated response element promotor activation assay to evaluate the antagonistic capacity of SARS-CoV-2 wild-type ORF6 constructs and three mutants (Gln51Glu, Gln56Glu, or both) that represent amino acid substitutions between SARS-CoV and SARS-CoV-2 protein 6 in the carboxy-terminal domain.FindingsOverall, replication was higher for SARS-CoV in Vero E6 cells and for SARS-CoV-2 in Calu-3 cells. SARS-CoV-2 was reliant on TMPRSS2, found only in Calu-3 cells, for more efficient entry. SARS-CoV-2 was more sensitive to interferon treatment, less efficient in suppressing cytokine induction via IRF3 nuclear translocation, and permissive of a higher level of induction of interferon-stimulated genes MX1 and ISG56. SARS-CoV-2 ORF6 expressed in the context of a fully replicating SARS-CoV backbone suppressed MX1 gene induction, but this suppression was less efficient than that by SARS-CoV ORF6. Mutagenesis showed that charged amino acids in residues 51 and 56 shift the phenotype towards more efficient interferon antagonism, as seen in SARS-CoV.InterpretationSARS-CoV-2 ORF6 interferes less efficiently with human interferon induction and interferon signalling than SARS-CoV ORF6. Because of the homology of the genes, onward selection for fitness could involve functional optimisation of interferon antagonism. Charged amino acids at positions 51 and 56 in ORF6 should be monitored for potential adaptive changes.FundingBundesministerium für Bildung und Forschung, EU RECOVER project.

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Engineering SARS-CoV-2 using a reverse genetic system.

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