Regulation of<i>toxA</i>by PtxR in<i>Pseudomonas aeruginosa</i>PA103
Bibliographic record
Abstract
Exotoxin A (ETA) production in Pseudomonas aeruginosa requires the regulatory locus regAB. Pseudomonas aeruginosa PA103 produces significantly higher levels of ETA than the prototypic strain PAO1 does, partly because of differences in the regAB locus. Other factors that contribute to this variation are not known. We previously described the P. aeruginosa gene ptxR that positively regulates production of ETA through regAB. ETA production was enhanced but still iron regulated in the PAO1 strain PAO1-XR that carries two copies of ptxR on its chromosome. Here we determine whether ptxR regulation of ETA is different in PA103. In contrast to PAO1-XR, ETA activity produced by PA103-2R, a PA103 strain carrying two copies of ptxR, is enhanced tenfold and partially deregulated in the presence of iron. Real-time PCR transcriptional analysis showed that the copy number of toxA mRNA in PA103-2R is significantly higher than in PA103 in both the presence and absence of iron, yet no similar increase in either regAB or ptxR mRNA copy number was detected. The integrated plasmid together with adjoining DNA was retrieved from the PA103-2R chromosome to determine whether integration-induced DNA changes played a role in this phenotype. Introduction of the retrieved plasmid in PA103 produced a phenotype similar to that of PA103-2R. Sequence analysis of the plasmid revealed the loss of 322 bp within the region 3' of ptxR. A plasmid construct carrying a 4-bp insertion in this same region produced in PA103 a phenotype similar to that of PA103-2R. Our results suggest that the effect of ptxR on toxA expression is different in PA103 than in PAO1 and that this variation in PA103-2R does not occur solely through regAB. Changes within the region 3' of ptxR are critical for the production of the unique PA103-2R phenotype, which occurs in trans and requires intact ptxR, but is not caused by ptxR overexpression.
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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 | 0.001 |
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".