The mitochondrial proteome of diplonemids: from conventional pathways to eccentric RNA editing and transcript processing
Bibliographic record
Abstract
BACKGROUND: Diplonemids constitute an abundant and geographically widespread but little-studied group of marine protists. A hallmark of this lineage, the kinetoplastid sister group within Euglenozoa, is a mitochondrial genome comprising numerous small circular DNA molecules that carry fragments of mitochondrial genes. Complex RNA processing of the corresponding transcripts involves numerous ligation and RNA editing steps in the production of mature RNA species. To assess the diplonemid mitochondrial proteome and, in particular, to search for proteins that might mediate RNA processing, we undertook a comprehensive in silico analysis to predict candidate mitochondrial proteins in the type species Diplonema papillatum. RESULTS: Using sequence similarity searches in conjunction with a mitochondrial targeting pipeline, we identified at least 1878 candidate nucleus-encoded mitochondrial proteins in addition to 16 mitochondrion-encoded proteins described previously. Despite the highly unconventional nature of the mitochondrial genome in D. papillatum, its mitochondrial proteome (mitoproteome) contains virtually all the functionally most important proteins that are ubiquitous among aerobic mitochondria, and several novel proteins that have been recruited in the euglenozoan last common ancestor to augment complexes involved in coupled electron transport oxidative phosphorylation and mitochondrial ribosome formation. Notably, we identified several individual proteins and multi-protein families that are candidates for RNA ligation and editing enzymes. CONCLUSIONS: This first comprehensive mitoproteome data for a diplonemid, together with published mitoproteome data for other members of Discoba, allows us to make inferences about marked changes in mitochondrial structure and function that have occurred since the divergence of diplonemids and other euglenozoans from the last common discobid ancestor.
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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 | 0.000 |
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".