<i>E. coli</i> 6S RNA complexed to RNA polymerase maintains product RNA synthesis at low cellular ATP levels by initiation with non-canonical initiator nucleotides
Bibliographic record
Abstract
The E. coli 6S RNA is an RNA polymerase (RNAP) inhibitor that competes with σ70-dependent DNA promoters for binding to RNAP holoenzyme (RNAP:σ70). The 6S RNA when bound is then used as a template to synthesize a short product RNA (pRNA; usually 13-nt-long). This pRNA changes the 6S RNA structure, triggering the 6S RNA:pRNA complex to release and allowing DNA-dependent housekeeping gene expression to resume. In high nutrient conditions, 6S RNA turnover is extremely rapid but becomes very slow in low nutrient environments. This leads to a large accumulation of inhibited RNAP:σ70 complex in stationary phase. As pRNA initiates synthesis with ATP, we and others have proposed that the 6S RNA release rate strongly depends on ATP levels as a proxy for sensing the cellular metabolic state. By purifying endogenous 6S RNA:pRNA complexes using RNA Mango and by using reverse transcriptase to generate pRNA-cDNA chimeras, we demonstrate that 6S RNA:pRNA formation can be simultaneous with 6S 5' maturation. More importantly, we find a dramatic accumulation of capped pRNAs during stationary phase. This indicates that ATP levels in stationary phase are low enough for non-canonical initiator nucleotides (NCINs) such as NAD+ and NADH to initiate pRNA synthesis. In vitro, mutation of the well conserved 6S template sequence immediately upstream of the pRNA transcriptional start site can increase or decrease the pRNA capping efficiency, suggesting that evolution has tuned the biological 6S RNA sequence for an optimal capping rate in low nutrient conditions. NCIN-initiated pRNA synthesis may therefore be essential for cell viability in low nutrient conditions when ATP concentrations are low.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".