Generation of a SARS-CoV-2 reverse genetics system and novel human lung cell lines that exhibit high virus-induced cytopathology
Bibliographic record
Abstract
Abstract The global COVID-19 pandemic continues with an increasing number of cases worldwide and the emergence of new SARS-CoV-2 variants. In our study, we have developed novel tools with applications for screening antivirals, identifying virus-host dependencies, and characterizing viral variants. Using reverse genetics, we rescued SARS-CoV-2 Wuhan1 (D614G variant) wild type (WTFL) and reporter virus (NLucFL) using molecular BAC clones. The replication kinetics, plaque morphology and titers were comparable between rescued molecular clones and a clinical isolate (VIDO-01 strain), thus providing confidence that the rescued viruses can be used as effective replication tools. Furthermore, the reporter SARS-CoV-2 NLucFL virus exhibited robust luciferase values over the time course of infection and was used to develop a rapid antiviral assay using remdesivir as proof-of-principle. In addition, as a tool to study lung-relevant virus-host interactions, we established novel human lung cell lines that support SARS-CoV-2 infection with high virus-induced cytopathology. Six lung cell lines (NCI-H23, A549, NCI-H1703, NCI-H520, NCI-H226, and HCC827) and HEK293T cells, were transduced to stably express ACE2 and tested for their ability to support virus infection. A549 ACE2 B1 and HEK293T ACE2 A2 cell lines exhibited more than 70% virus-induced cell death and a novel lung cell line NCI-H23 ACE2 A3 showed about ∼99% cell death post-infection. These cell lines are ideal for assays relying on live-dead selection and are currently being used in CRISPR knockout and activation screens in our lab. Importance We used a reverse genetics system to generate a wild type as well as a nanoluciferase-expressing reporter clone of SARS-CoV-2. The reporter virus allows for rapid transient replication assays and high throughput screens by detection of virus replication using luciferase assays. In addition, the reverse genetic system can be used to generate mutant viruses to study phenotypes of variant mutations. Additionally, unique human lung cell lines supporting SARS-CoV-2 replication will aid in studying the virus in a lung-relevant environment and based on high cytopathology induced in some cell lines, will be useful for screens that rely on virus-induced cell death for selection. Our study aims to enhance and contribute to the current replication tools available to study SARS-CoV-2 by providing rapid methods, virus clones and novel lung cell lines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".