Loss of RNase R Induces Competence Development in <i>Legionella pneumophila</i>
Bibliographic record
Abstract
RNase R is a processive 3'-5' exoribonuclease with a high degree of conservation in prokaryotes. Although some bacteria possess additional hydrolytic 3'-5' exoribonucleases such as RNase II, RNase R was found to be the only predicted one in the facultative intracellular pathogen Legionella pneumophila. This provided a unique opportunity to study the role of RNase R in the absence of an additional RNase with similar enzymatic activity. We investigated the role of RNase R in the biology of Legionella pneumophila under various conditions and performed gene expression profiling using microarrays. At optimal growth temperature, the loss of RNase R had no major consequence on bacterial growth and had a moderate impact on normal gene regulation. However, at a lower temperature, the loss of RNase R had a significant impact on bacterial growth and resulted in the accumulation of structured RNA degradation products. Concurrently, gene regulation was affected and specifically resulted in an increased expression of the competence regulon. Loss of the exoribonuclease activity of RNase R was sufficient to induce competence development, a genetically programmed process normally triggered as a response to environmental stimuli. The temperature-dependent expression of competence genes in the rnr mutant was found to be independent of previously identified competence regulators in Legionella pneumophila. We suggest that a physiological role of RNase R is to eliminate structured RNA molecules that are stabilized by low temperature, which in turn may affect regulatory networks, compromising adaptation to cold and thus resulting in decreased viability.
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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".