Analysis of Porcine RIG-I Like Receptors Revealed the Positive Regulation of RIG-I and MDA5 by LGP2
Bibliographic record
Abstract
The RLRs play critical roles in sensing and fighting viral infections especially RNA virus infections. Despite the extensive studies on RLRs in humans and mice, there is a lack of systemic investigation of livestock animal RLRs. In this study, we characterized the porcine RLR members RIG-I, MDA5 and LGP2. Compared with their human counterparts, porcine RIG-I and MDA5 exhibited similar signaling activity to distinct dsRNA and viruses, via similar and cooperative recognitions. Porcine LGP2, without signaling activity, was found to positively regulate porcine RIG-I and MDA5 in transfected porcine alveolar macrophages (PAMs), gene knockout PAMs and PK-15 cells. Mechanistically, LGP2 interacts with RIG-I and MDA5 upon cell activation, and promotes the binding of dsRNA ligand by MDA5 as well as RIG-I. Accordingly, porcine LGP2 exerted broad antiviral functions. Intriguingly, we found that porcine LGP2 mutants with defects in ATPase and/or dsRNA binding present constitutive activity which are likely through RIG-I and MDA5. Our work provided significant insights into porcine innate immunity, species specificity and immune biology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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 teacher head, 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".