The <i>Burkholderia cenocepacia</i> sensor kinase hybrid AtsR is a global regulator modulating quorum‐sensing signalling
Bibliographic record
Abstract
Burkholderia cenocepacia is commonly found in the environment and also as an important opportunistic pathogen infecting patients with cystic fibrosis. Successful infection by this bacterium requires coordinated expression of virulence factors, which is achieved through different quorum sensing (QS) regulatory systems. Biofilm formation and Type 6 secretion system (T6SS) expression in B. cenocepacia K56-2 are positively regulated by QS and negatively regulated by the sensor kinase hybrid AtsR. This study reveals that in addition to affecting biofilm and T6SS activity, the deletion of atsR in B. cenocepacia leads to overproduction of other QS-regulated virulence determinants including proteases and swarming motility. Expression of the QS genes, cepIR and cciIR, was upregulated in the ΔatsR mutant and resulted in early and increased N-acylhomoserine lactone (AHL) production, suggesting that AtsR plays a role in controlling the timing and fine-tuning of virulence gene expression by modulating QS signalling. Furthermore, a ΔatsRΔcepIΔcciI mutant could partially upregulate the same virulence determinants indicating that AtsR also modulates the expression of virulence genes by a second mechanism, independently of any AHL production. Together, our results strongly suggest that AtsR is a global virulence regulator in B. cenocepacia.
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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".