Riboswitch and small RNAs modulate <i>btuB</i> translation initiation in <i>Escherichia coli</i> and trigger distinct mRNA regulatory mechanisms
Bibliographic record
Abstract
Small RNAs (sRNAs) and riboswitches represent distinct classes of RNA regulators that control gene expression upon sensing metabolic or environmental variations. While sRNAs and riboswitches regulate gene expression by affecting mRNA and protein levels, existing studies have been limited to the characterization of each regulatory system in isolation, suggesting that sRNAs and riboswitches target distinct mRNA populations. We report that the expression of btuB in Escherichia coli, which is regulated by an adenosylcobalamin (AdoCbl) riboswitch, is also controlled by the small RNAs OmrA and, to a lesser extent, OmrB. Strikingly, we find that the riboswitch and sRNAs reduce mRNA levels through distinct pathways. Our data show that while the riboswitch triggers Rho-dependent transcription termination, sRNAs rely on the degradosome to modulate mRNA levels. Importantly, OmrA pairs with the btuB mRNA through its central region, which is not conserved in OmrB, indicating that these two sRNAs may have specific targets in addition to their common regulon. In contrast to canonical sRNA regulation, we find that OmrA repression of btuB is lost using an mRNA binding-deficient Hfq variant. Together, our study demonstrates that riboswitch and sRNAs modulate btuB expression, providing an example of cis- and trans-acting RNA-based regulatory systems maintaining cellular homeostasis.
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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 | 0.000 |
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".