Characterization of the orf1‐tolQRA operon in <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
The tol-pal genes play important roles in maintaining outer membrane integrity, transmembrane transportation, and cell division in Gram-negative bacteria. In Pseudomonas aeruginosa, an important human opportunistic pathogen, the tol-oprL genes are organized uniquely in three operons, orf1-tolQRA, tolB and oprL-orf2, and are regulated by iron availability. Similarity between TolQRA and the iron transport system ExbBD-TonB also exists in P. aeruginosa and they can replace each other imperfectly. It is of importance to investigate the regulation and functions of this membrane complex. In the present study, we characterized the promoters and expression profiles of the orf1-tolQRA operon and investigated the function of Orf1. Primer extension was carried out by using both isotope-labeled and florescence labeled primers and the expression profiles were determined using both lacZ and luxCDABE-based transcriptional fusions. Our results revealed two distinct promoters at the upstream region of tolQRA; the one located in front of orf1 was constitutive whereas the other within the orf1 coding region was iron regulated. Expression profiles indicate the tol genes were also downregulated by the quorum-sensing systems during the late stage of growth. Unlike tolQ and tolA, we were able to construct a viable orf1 knockout strain, and the mutant exhibited altered cell and colony morphology, providing first evidence that Orf1 plays a non-essential role in the Tol-OprL complex in P. aeruginosa.
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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 | 0.000 |
| 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".