Mistranslating tRNA variants have anticodon- and sex-specific impacts on <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
ABSTRACT Transfer RNAs (tRNAs) are vital in determining the specificity of translation. Mutations in tRNA genes can result in the misincorporation of amino acids into nascent polypeptides in a process known as mistranslation. Since mistranslation has different impacts, depending on the type of amino acid substitution, our goal here was to compare the impact of different mistranslating tRNA Ser variants on fly development, lifespan, and behaviour. We established two mistranslating fly lines, one with a tRNA Ser variant that misincorporates serine at valine codons (V➔S) and the other that misincorporates serine at threonine codons (TàS). While both mistranslating tRNAs increased development time and developmental lethality, the severity of the impacts differed depending on amino acid substitution and sex. The V➔S variant extended embryonic, larval, and pupal development whereas the T➔S only extended larval and pupal development. Females, but not males, containing either mistranslating tRNA presented with significantly more anatomical deformities than controls. Mistranslating females also experienced extended lifespan whereas mistranslating male lifespan was unaffected. In addition, mistranslating flies from both sexes showed improved locomotion as they aged, suggesting delayed neurodegeneration. Therefore, although mistranslation causes detrimental effects, we demonstrate that mistranslation also has positive effects on complex traits such as lifespan and locomotion. This has important implications for human health given the prevalence of tRNA variants in humans. PLAIN LANGUAGE SUMMARY Mutant tRNA genes can cause mistranslation, the misincorporation of amino acids into proteins, and are associated with several human diseases. This study investigated the role of two tRNA variants that cause threonine-to-serine (T➔S) or valine-to-serine (V➔S) substitution. Both variants caused developmental delays and lethality in both sexes and increase prevalence of deformities in females. Surprisingly, female T➔S and V➔S flies experienced increased lifespan and mistranslating males and females showed improved locomotion. These results suggest that mistranslation has both positive and negative effects that depend on the tRNA variant and sex of the fly.
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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) | 0.002 | 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 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".