Mutational Analysis of Trypanosoma brucei RNA Editing Ligase Reveals Regions Critical for Interaction with KREPA2
Bibliographic record
Abstract
The Trypanosoma brucei parasite causes the vector-borne disease African sleeping sickness. Mitochondrial mRNAs of T. brucei undergo posttranscriptional RNA editing to make mature, functional mRNAs. The final step of this process is catalyzed by the essential ligase, T. brucei RNA Editing Ligase 1 (TbREL1) and the closely related T. brucei RNA Editing Ligase 2 (TbREL2). While other ligases such as T7 DNA ligase have both a catalytic and an oligonucleotide/oligosaccharide-binding (OB)-fold domain, T. brucei RNA editing ligases contain only the catalytic domain. The OB-fold domain, which is required for interaction with the substrate RNA, is provided in trans by KREPA2 (for TbREL1) and KREPA1 (for TbREL2). KREPA2 enhancement of TbREL1 ligase activity is presumed to occur via an OB-fold-mediated increase in substrate specificity and catalysis. We characterized the interaction between TbREL1 and KREPA2 in vitro using full-length, truncated, and point-mutated ligases. As previously shown, our data indicate strong, specific stimulation of TbREL1 catalytic activity by KREPA2. We narrowed the region of contact to the final 59 C-terminal residues of TbREL1. Specifically, the TbREL1 C-terminal KWKE (441-444) sequence appear to coordinate the KREPA2-mediated enhancement of TbREL1 activities. N-terminal residues F206, T264 and Y275 are crucial for the overall activity of TbREL1, particularly for F206, a mutation of this residue also disrupts KREPA2 interaction. Thus, we have identified the critical TbREL1 regions and amino acids that mediate the KREPA2 interaction.
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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 | 0.001 |
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".