mRNA Composition and Control of Bacterial Gene Expression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The expression of any given bacterial protein is predicted to depend on (i) the transcriptional regulation of the promoter and the translational regulation of its mRNA and (ii) the synthesis and translation of total (bulk) mRNA. This is because total mRNA acts as a competitor to the specific mRNA for the binding of initiation-ready free ribosomes. To characterize the effects of mRNA competition on gene expression, the specific activity of beta-galactosidase expressed from three different promoter-lacZ fusions (P(spc)-lacZ, P(RNAI)-lacZ, and P(RNAII)-lacZ) was measured (i) in a relA(+) background during exponential growth at different rates and (ii) in relA(+) and DeltarelA derivatives of Escherichia coli B/r after induction of a mild stringent or a relaxed response to raise or lower, respectively, the level of ppGpp. Expression from all three promoters was stimulated during slow exponential growth or at elevated levels of ppGpp and was reduced during fast exponential growth or at lower levels of ppGpp. From these observations and from other considerations, we propose (i) that the concentration of free, initiation-ready ribosomes is approximately constant and independent of the growth rate and (ii) that bulk mRNA made during slow growth and at elevated levels of ppGpp is less efficiently translated than bulk mRNA made during fast growth and at reduced levels of ppGpp. These features lead to an indirect enhancement in the expression of LacZ (or of any other protein) during growth in media of poor nutritional quality and at increased levels of ppGpp.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it