Mitochondrial tRNA 5′-Editing in Dictyostelium discoideum and Polysphondylium pallidum
Bibliographic record
Abstract
Mitochondrial tRNA (mt-tRNA) 5'-editing was first described more than 20 years ago; however, the first candidates for 5'-editing enzymes were only recently identified in a eukaryotic microbe (protist), the slime mold Dictyostelium discoideum. In this organism, eight of 18 mt-tRNAs are predicted to be edited based on the presence of genomically encoded mismatched nucleotides in their aminoacyl-acceptor stem sequences. Here, we demonstrate that mt-tRNA 5'-editing occurs at all predicted sites in D. discoideum as evidenced by changes in the sequences of isolated mt-tRNAs compared with the expected sequences encoded by the mitochondrial genome. We also identify two previously unpredicted editing events in which G-U base pairs are edited in the absence of any other genomically encoded mismatches. A comparison of 5'-editing in D. discoideum with 5'-editing in another slime mold, Polysphondylium pallidum, suggests organism-specific idiosyncrasies in the treatment of U-G/G-U pairs. In vitro activities of putative D. discoideum editing enzymes are consistent with the observed editing reactions and suggest an overall lack of tRNA substrate specificity exhibited by the repair component of the editing enzyme. Although the presence of terminal mismatches in mt-tRNA sequences is highly predictive of the occurrence of mt-tRNA 5'-editing, the variability in treatment of U-G/G-U base pairs observed here indicates that direct experimental evidence of 5'-editing must be obtained to understand the complete spectrum of mt-tRNA editing events in any species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".