Binding properties of YjeQ (RsgA), RbfA, RimM and Era to assembly intermediates of the 30S subunit
Bibliographic record
Abstract
Our understanding regarding the function of YjeQ (also called RsgA), RbfA, RimM and Era in ribosome biogenesis has been derived in part from the study of immature 30S particles that accumulate in null strains lacking one of these factors. However, their mechanistic details are still unknown. Here, we demonstrate that these immature particles are not dead-end products of assembly, but progress into mature 30S subunits. Mass spectrometry analysis revealed that in vivo the occupancy level of these factors in these immature 30S particles is below 10% and that the concentration of factors does not increase when immature particles accumulate in cells. We measured by microscale thermophoresis that YjeQ and Era binds to the mature 30S subunit with high affinity. However, the binding affinity of these factors to the immature particles and of RimM and RbfA to mature or immature particles was weak, suggesting that binding is not occurring at physiological concentrations. These results suggest that in the absence of these factors, the immature particles evolve into a thermodynamically stable intermediate that exhibits low affinity for the assembly factors. These results imply that the true substrates of YjeQ, RbfA, RimM and Era are immature particles that precede the ribosomal particles accumulating in the knockouts strains.
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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 | 0.001 |
| 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".