RegA, Iron, and Growth Phase Regulate Expression of the <i>Pseudomonas aeruginosa tol-oprL</i> Gene Cluster
Bibliographic record
Abstract
The tol-oprL region in Pseudomonas aeruginosa appears to be involved in pyocin uptake and required for cell viability. The complete nucleotide sequences of the tolQRA and oprL genes as well as the incomplete sequences of tolB and orf2 have been previously reported. In addition, the sequence of a P. aeruginosa iron-regulated gene (pig6) has been described and found to share homology with an open reading frame located upstream of the Escherichia coli tolQRA genes (U. A. Ochsner and M. L. Vasil, Proc. Natl. Acad. Sci. USA 93:4409-4414, 1996). In this study, we cloned the remainder of the P. aeruginosa tol-oprL gene cluster and determined its nucleotide sequence. This cluster was found to consist of seven genes in the order orf1 tolQ tolR tolA tolB oprL orf2. Transcriptional analysis of this gene cluster was performed by detecting the presence of mRNAs spanning adjacent genes as well as by using a promoterless lacZ reporter gene fused to each of the seven genes contained in the tol-oprL locus. The results show that there are three major transcriptional units or operons in this region, orf1-tolQRA, tolB, and oprL-orf2, in contrast to the E. coli tol-pal region, where there are only two operons, orf1-tolQRA and tolB-pal-orf2. Analysis of gene expression indicated that the tol-oprL genes of P. aeruginosa are both iron and growth phase modulated. The first operon, orf1-tolQRA, is iron regulated throughout growth, but iron-regulated expression of tolB and oprL fusions occurs only in late log phase. The expression of the three operons was significantly less repressed by iron in fur mutants than in the wild-type strain, suggesting the involvement of Fur in the iron regulation of all three operons. RegA is a positive yet nonessential regulator of tol-oprL expression.
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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 | 0.001 |
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".