Dual-level autoregulation of the <i>E. coli</i> DeaD RNA helicase via mRNA stability and Rho-dependent transcription termination
Bibliographic record
Abstract
DEAD-box proteins (DBPs) are RNA remodeling factors associated with RNA helicase activity that are found in nearly all organisms. Despite extensive studies on the mechanisms used by DBPs to regulate RNA function, very little is known about how DBPs themselves are regulated. In this work, we have analyzed the expression and regulation of DeaD/CsdA, the largest of the DBPs in Escherichia coli ( E. coli ). We show that deaD transcription initiates 838 nt upstream of the start of the coding region. We have also found that DeaD is autoregulated through a negative feedback mechanism that operates both at the level of deaD mRNA stability and Rho-dependent transcription termination, and this regulation is dependent upon its mRNA 5′ untranslated region (5′ UTR). These findings suggest that DeaD might be regulating the conformation of its own mRNA through its RNA helicase activity to facilitate ribonuclease and Rho access to its 5′ UTR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".