Functional MDA5 knockout in CHSE-214 cells decreases the response to long dsRNA and enhances Chum Salmon Reovirus susceptibility
Bibliographic record
Abstract
Many organisms express sensors that detect long dsRNA, a nucleic acid produced by almost all viruses during replication. These subcellular compartment-specific pattern recognition receptors (PRRs) detect viral replication and rapidly induce a generalist immune response mediated by type I interferon and interferon-stimulated genes (ISGs). In this study, the role of melanoma differentiation-associated protein (MDA)5, a cytoplasmic sensor of long dsRNA, was measured in CHSE-214 cells that have been genetically modified for MDA5 to either to be non-functional (frameshift mutation; MDA5C1) or have a silent point mutation (MDA5C2). These cells were transfected with long dsRNA of either 659bp or 334bp in length, and their ability to induce ISG transcript expression (Mx1, vig-3 and vig-4) was measured by RT-qPCR. MDA5C1 produced significantly less Mx1, vig-3 and vig-4 transcripts compared to MDA5C2 when treated with the 659bp dsRNA molecule, while there was no difference between cell lines in Mx1 expression levels when induced by a 334 bp dsRNA molecule. MDA5C1 was more susceptible to CSV than MDA5C2, and dsRNA treatment was able to protect both cell lines from CSV infection. However, there were no length dependent effects observed, nor were there differences in dsRNA-mediated protection between cell lines. This data suggests that salmonid MDA5 has a length preference similar to mammals, with longer dsRNA molecules being better ligands for this receptor. It also suggests that MDA5 may play a role in the antiviral response against CSV but the antiviral response is not dependent on MDA5. These are important findings for understanding the fundamental importance of MDA5 in the antiviral response of salmonids.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".