The iron-sensing aconitase B binds its own mRNA to prevent sRNA-induced mRNA cleavage
Bibliographic record
Abstract
Aconitase is an iron-sulfur protein and a major enzyme of the TCA cycle that catalyzes the conversion of citrate to isocitrate under iron-rich conditions. In Escherichia coli, aconitase B (AcnB) is a typical moonlighting protein that can switch to its apo form (apo-AcnB) which favors binding its own mRNA 3'UTR and stabilize it when intracellular iron become scarce. The small regulatory RNA (sRNA) RyhB has previously been shown to promote RNase E-dependent degradation of acnB mRNA when it was expressed from an ectopic arabinose-dependent promoter, independently of intracellular iron levels. In marked contrast, we report here that expression of RyhB under low-iron conditions did not result in acnB mRNA degradation even when RyhB was bound to acnB ribosome binding site (RBS). Genetic and biochemical evidence suggested that, under low-iron conditions, apo-AcnB bound to acnB 3'UTR close to a RNase E cleavage site that is essential for RyhB-induced acnB mRNA degradation. Whereas RyhB can block acnB translation initiation, RNase E-dependent degradation of acnB was prevented by apo-AcnB binding close to the cleavage site. This previously uncharacterized regulation suggests an intricate post-transcriptional mechanism that represses protein expression while insuring mRNA stability.
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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".