The OxyR-regulated phnW gene encoding 2-aminoethylphosphonate:pyruvate aminotransferase helps protect Pseudomonas aeruginosa from tert-butyl hydroperoxide
Bibliographic record
Abstract
The LysR member of bacterial transactivators, OxyR, governs transcription of genes involved in the response to H2O2 and organic (alkyl) hydroperoxides (AHP) in the Gram-negative pathogen, Pseudomonas aeruginosa. We have previously shown that organisms lacking OxyR are rapidly killed by <2 or 500 mM H2O2 in planktonic and biofilm bacteria, respectively. In this study, we first employed a bioinformatic approach to elucidate the potential regulatory breadth of OxyR by scanning the entire P. aeruginosa PAO1 genome for canonical OxyR promoter recognition sequences (ATAG-N7-CTAT-N7-ATAG-N7-CTAT). Of >100 potential OxyR-controlled genes, 40 were strategically selected that were not predicted to be involved in the direct response to oxidative stress (e.g., catalase, peroxidase, etc.) and screened such genes by RT-PCR analysis for potentially positive or negative control by OxyR. Differences were found in 7 of 40 genes when comparing an oxyR mutant vs. PAO1 expression that was confirmed by ß-galactosidase reporter assays. Among these, phnW, encoding 2-aminoethylphosphonate:pyruvate aminotransferase, exhibited reduced expression in the oxyR mutant compared to wild-type bacteria. Electrophoretic mobility shift assays indicated binding of OxyR to the phnW promoter and DNase I footprinting analysis also revealed the sequences to which OxyR bound. Interestingly, a phnW mutant was more susceptible to t-butyl-hydroperoxide (t-BOOH) treatment than wild-type bacteria. Although we were unable to define the direct mechanism underlying this phenomenon, we believe that this may be due to a reduced efficiency for this strain to degrade t-BOOH relative to wild-type organisms because of modulation of AHP gene transcription in the phnW mutant.
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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) | 0.001 | 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) | 0.001 | 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".