Role of the sarcin-ricin loop of 23S rRNA in biogenesis of the 50S ribosomal subunit
Bibliographic record
Abstract
The sarcin-ricin loop (SRL) is one of the most conserved segments of ribosomal RNA (rRNA). Translational GTPases (trGTPases), such as EF-G, EF-Tu, and IF2, form contacts with the SRL that are critical for GTP hydrolysis and factor function. Previous studies showed that expression of 23S rRNA lacking the SRL confers a dominant lethal phenotype inEscherichia coli. Isolated ΔSRL particles were found to be not only inactive in protein synthesis but also incompletely assembled. In particular, block 4 of the subunit, which includes the peptidyl transferase center, remained unfolded. Here, we explore the basis of this assembly defect. We find that 23S rRNA extracted from ΔSRL subunits can be efficiently reconstituted into 50S subunits, and these reconstituted ΔSRL particles exhibit full peptidyl transferase activity. We also further characterize ΔSRL particles purified from cells, using cryo-EM and proteomic methods. These particles lack density for rRNA and r-proteins of block 4, consistent with earlier chemical probing data. Incubation of these particles with excess total r-protein of the large subunit (TP50) fails to restore substantial peptidyl transferase activity. Interestingly, proteomic analysis of control and mutant particles shows an overrepresentation of multiple assembly factors in the ΔSRL case. We propose that one or more GTPases normally act to release assembly factors, and this activity is blocked in the absence of the SRL.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".