Pseudomonas aeruginosa displays a dormancy phenotype during long-term survival in water
Bibliographic record
Abstract
Pseudomonas aeruginosa is capable of long-term survival in water, which may serve as a reservoir for infection. Although viable cell counts of PAO1 incubated in water remain stable throughout 8 weeks, LIVE/DEAD staining indicated a high proportion of cells stained with propidium iodide (PI). The proportion of PI-stained cells increased by 4 weeks, then decreased again by 8 weeks, suggesting an adaptive response. This was also evident in an observed shift in cell morphology from a rod to a coccoid shape after 8 weeks. Fluorescence-activated cell sorting (FACS) was used to recover PI-stained cells, which were plated and shown to be viable, indicating that PI-stained cells were membrane-compromised but still cultivable. PAO1 mid-log cells in water were labeled with the dsDNA-binding dye PicoGreen to monitor viability as well as DNA integrity, which demonstrated that the population remains viable and transitions towards increased dsDNA staining. Metabolic activity was found to decrease significantly in water by 4 weeks. The PAO1 outer membrane became less permeable and more resistant to polymyxin B damage in water, and the profile of total membrane lipids changed over time. Among the ~1400 transcriptional lux fusions, gene expression in water revealed that the majority of genes were repressed, but subsets of genes were induced at particular time points. In summary, these results indicate that P. aeruginosa is dormant in water and this adaptation involves a complex pattern of gene regulation and changes to the cell to promote long-term survival and antibiotic tolerance. The approach of P. aeruginosa incubated in water may be useful to study antibiotic tolerance and the mechanisms of dormancy and survival in nutrient limiting conditions.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".