Prion gene paralogs are dispensable for early zebrafish development and have nonadditive roles in seizure susceptibility
Bibliographic record
Abstract
Normally folded prion protein (PrP C ) and its functions in healthy brains remain underappreciated compared with the intense study of its misfolded forms ("prions," PrP Sc ) during the pathobiology of prion diseases. This impedes the development of therapeutic strategies in Alzheimer's and prion diseases. Disrupting the zebrafish homologs of PrP C has provided novel insights; however, mutagenesis of the zebrafish paralog prp2 did not recapitulate previous dramatic developmental phenotypes, suggesting redundancy with the prp1 paralog. Here, we generated zebrafish prp1 loss–of–function mutant alleles and dual prp1 −/− ;prp2 −/− mutants. Zebrafish prp1 −/− and dual prp1 −/− ;prp2 −/− mutants resemble mammalian Prnp knockouts insofar as they lack overt phenotypes, which surprisingly contrasts with reports of severe developmental phenotypes when either prp1 or prp2 is knocked down acutely. Previous studies suggest that PrP C participates in neural cell development/adhesion, including in zebrafish where loss of prp2 affects adhesion and deposition patterns of lateral line neuromasts. In contrast with the expectation that prp1 's functions would be redundant to prp2 , they appear to have opposing functions in lateral line neurodevelopment. Similarly, loss of prp1 blunted the seizure susceptibility phenotypes observed in prp2 mutants, contrasting the expected exacerbation of phenotypes if these prion gene paralogs were serving redundant roles. In summary, prion mutant fish lack the overt phenotypes previously predicted, and instead they have subtle phenotypes similar to mammals. No evidence was found for functional redundancy in the zebrafish prion gene paralogs, and the phenotypes observed when each gene is disrupted individually are consistent with ancient functions of prion proteins in neurodevelopment and modulation of neural activity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".