Transcriptomic changes of Legionella pneumophila in water
Bibliographic record
Abstract
BACKGROUND: Legionella pneumophila (Lp) is a water-borne opportunistic pathogen. In water, Lp can survive for an extended period of time until it encounters a permissive host. Therefore, identifying genes that are required for survival in water may help develop strategies to prevent Legionella outbreaks. RESULTS: We compared the global transcriptomic response of Lp grown in a rich medium to that of Lp exposed to an artificial freshwater medium (Fraquil) for 2, 6 and 24 hours. We uncovered successive changes in gene expression required for the successful adaptation to a nutrient-limited water environment. The repression of major pathways involved in cell division, transcription and translation, suggests that Lp enters a quiescent state in water. The induction of flagella associated genes (flg, fli and mot), enhanced-entry genes (enh) and some Icm/Dot effector genes suggests that Lp is primed to invade a suitable host in response to water exposure. Moreover, many genes involved in resistance to antibiotic and oxidative stress were induced, suggesting that Lp may be more tolerant to these stresses in water. Indeed, Lp exposed to water is more resistant to erythromycin, gentamycin and kanamycin than Lp cultured in rich medium. In addition, the bdhA gene, involved in the degradation pathway of the intracellular energy storage compound polyhydroxybutyrate, is also highly expressed in water. Further characterization show that expression of bdhA during short-term water exposure is dependent upon RpoS, which is required for the survival of Lp in water. Deletion of bdhA reduces the survival of Lp in water at 37 °C. CONCLUSIONS: The increase of antibiotic resistance and the importance of bdhA to the survival of Lp in water seem consistent with the observed induction of these genes when Lp is exposed to water. Other genes that are highly induced upon exposure to water could also be necessary for Lp to maintain viability in the water environment.
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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".