Extracellular DNA controls expression of Pseudomonas aeruginosa genes involved in nutrient utilization, metal homeostasis, acid pH tolerance and virulence
Bibliographic record
Abstract
Introduction. Pseudomonas aeruginosa grows in extracellular DNA (eDNA)-enriched biofilms and infection sites. eDNA is generally considered to be a structural biofilm polymer required for aggregation and biofilm maturation. In addition, eDNA can sequester divalent metal cations, acidify growth media and serve as a nutrient source. Aim. We wanted to determine the genome-wide influence on the transcriptome of planktonic P. aeruginosa PAO1 grown in the presence of eDNA. Methodology. RNA-seq analysis was performed to determine the genome-wide effects on gene expression of PAO1 grown with eDNA. Transcriptional lux fusions were used to confirm eDNA regulation and to validate phenotypes associated with growth in eDNA. Results. The transcriptome of eDNA-regulated genes included 89 induced and 76 repressed genes (FDR<0.05). A large number of eDNA-induced genes appear to be involved in utilizing DNA as a nutrient. Several eDNA-induced genes are also induced by acidic pH 5.5, and eDNA/acidic pH promoted an acid tolerance response in P. aeruginosa . The cyoABCDE terminal oxidase is induced by both eDNA and pH 5.5, and contributed to the acid tolerance phenotype. Quantitative metal analysis confirmed that DNA binds to diverse metals, which helps explain why many genes involved in a general uptake of metals were controlled by eDNA. Growth in the presence of eDNA also promoted intracellular bacterial survival and influenced virulence in the acute infection model of fruit flies. Conclusion. The diverse functions of the eDNA-regulated genes underscore the important role of this extracellular polymer in promoting antibiotic resistance, virulence, acid tolerance and nutrient utilization; phenotypes that contribute to long-term survival.
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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".