Salmonid Double-stranded RNA–Dependent Protein Kinase Activates Apoptosis and Inhibits Protein Synthesis
Bibliographic record
Abstract
dsRNA-dependent protein kinase R (PKR) is a key factor of innate immunity. It is involved in translation inhibition, apoptosis, and enhancement of the proinflammatory and IFN responses. However, how these antiviral functions are conserved during evolution remains largely unknown. Overexpression and knockout studies in a Chinook salmon (Oncorhynchus tshawytscha) cell line were conducted to assess the role of salmonid PKR in the antiviral response. Three distinct mRNA isoforms from a unique pkr gene, named pkr-fl (full length), pkr-ml (medium length) and pkr-sl (short length), were cloned and a pkr-/- clonal fish cell line was developed using CRISPR/Cas9 genome editing. PKR-FL includes an N-terminal dsRNA-binding domain and a C-terminal kinase domain, whereas PKR-ML and PKR-SL display a truncated or absent kinase domain, respectively. PKR-FL is induced during IFNA2 stimulation but not during viral hemorrhagic septicemia virus (VHSV) infection. Overexpression experiments showed that only PKR-FL possesses antiviral functions, including activation of apoptosis and inhibition of de novo protein synthesis. Knockout experiments confirmed that PKR is involved in apoptosis activation during the late stage of VHSV infection. Endogenous PKR also plays a critical role in translation inhibition upon poly(I:C) transfection after IFNA2 treatment. It is, however, not involved in translational arrest during VHSV infection. Extra- and intracellular titrations showed that endogenous PKR does not directly inhibit viral replication but apparently favors virion release into the supernatant, likely by triggering late apoptosis. Altogether, our data confirm that salmonid PKR has conserved molecular functions that VHSV appears to bypass with subversion strategies.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".