A LysR-Type Transcriptional Regulator Controls Multiple Phenotypes in Acinetobacter baumannii
Bibliographic record
Abstract
Acinetobacter baumannii is a multidrug-resistant, Gram-negative nosocomial pathogen that exhibits phenotypic heterogeneity resulting in virulent opaque (VIR-O) and avirulent translucent (AV-T) colony variants. Each variant has a distinct gene expression profile resulting in multiple phenotypic differences. Cells interconvert between the VIR-O and AV-T variants at high frequency under laboratory conditions, suggesting that the genetic mechanism underlying the phenotypic switch could be manipulated to attenuate virulence. Therefore, our group has focused on identifying and characterizing genes that regulate this switch, which led to the investigation of ABUW_1132 (1132), a highly conserved gene predicted to encode a LysR-type transcriptional regulator. ABUW_1132 was shown to be a global regulator as the expression of 74 genes was altered ≥ 2-fold in an 1132 deletion mutant. The 1132 deletion also resulted in a 16-fold decrease in VIR-O to AV-T switching, loss of 3-OH-C12-HSL secretion, and reduced surface-associated motility. Further, the deletion of 1132 in the AV-T background caused elevated capsule production, which increased colony opacity and altered the typical avirulent phenotype of translucent cells. These findings distinguish 1132 as a global regulatory gene and advance our understanding of A. baumannii’s opacity-virulence switch.
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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) | 0.000 | 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 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".