The Phenotype of Many Independently Isolated +1 Frameshift Suppressor Mutants Supports a Pivotal Role of the P-Site in Reading Frame Maintenance
Bibliographic record
Abstract
The main features of translation are similar in all organisms on this planet and one important feature of it is the way the ribosome maintain the reading frame. We have earlier characterized several bacterial mutants defective in tRNA maturation and found that some of them correct a +1 frameshift mutation; i.e. such mutants possess an error in reading frame maintenance. Based on the analysis of the frameshifting phenotype of such mutants we proposed a pivotal role of the ribosomal grip of the peptidyl-tRNA to maintain the correct reading frame. To test the model in an unbiased way we first isolated many (467) independent mutants able to correct a +1 frameshift mutation and thereafter tested whether or not their frameshifting phenotypes were consistent with the model. These 467+1 frameshift suppressor mutants had alterations in 16 different loci of which 15 induced a defective tRNA by hypo- or hypermodifications or altering its primary sequence. All these alterations of tRNAs induce a frameshift error in the P-site to correct a +1 frameshift mutation consistent with the proposed model. Modifications next to and 3' of the anticodon (position 37), like 1-methylguanosine, are important for proper reading frame maintenance due to their interactions with components of the ribosomal P-site. Interestingly, two mutants had a defect in a locus (rpsI), which encodes ribosomal protein S9. The C-terminal of this protein contacts position 32-34 of the peptidyl-tRNA and is thus part of the P-site environment. The two rpsI mutants had a C-terminal truncated ribosomal protein S9 that destroys its interaction with the peptidyl-tRNA resulting in +1 shift in the reading frame. The isolation and characterization of the S9 mutants gave strong support of our model that the ribosomal grip of the peptidyl-tRNA is pivotal for the reading frame maintenance.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".