Maestro of regulation: Riboswitches orchestrate gene expression at the levels of translation, transcription and mRNA decay
Bibliographic record
Abstract
Riboswitches are RNA regulators that control gene expression by modulating their structure in response to metabolite binding. The study of mechanisms by which riboswitches modulate gene expression is crucial to understand how riboswitches are involved in maintaining cellular homeostasis. Previous reports indicate that riboswitches can control gene expression at the level of translation, transcription or mRNA decay. However, there are very few described examples where riboswitches regulate multiple steps in gene expression. Recent studies of a translation-regulating, TPP-dependent riboswitch have revealed that ligand binding is also involved in the control of mRNA levels. In this model, TPP binding to the riboswitch leads to the inhibition of translation, which in turn allows for Rho-dependent transcription termination. Thus, mRNA levels are indirectly controlled through ribosome occupancy. This is in contrast to other riboswitches that directly control mRNA levels by modulating the access of regulatory sequences involved in either Rho-dependent transcription termination or RNase E cleavage activity. Together, these findings indicate that riboswitches modulate both translation initiation and mRNA levels using multiple strategies that direct the outcome of gene expression.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".