A Novel Sensor Kinase-Response Regulator Hybrid Controls Biofilm Formation and Type VI Secretion System Activity in <i>Burkholderia cenocepacia</i>
Bibliographic record
Abstract
Burkholderia cenocepacia is an important opportunistic pathogen causing serious chronic infections in patients with cystic fibrosis (CF). Adaptation of B. cenocepacia to the CF airways may play an important role in the persistence of the infection. We have identified a sensor kinase-response regulator (BCAM0379) named AtsR in B. cenocepacia K56-2 that shares 19% amino acid identity with RetS from Pseudomonas aeruginosa. atsR inactivation led to increased biofilm production and a hyperadherent phenotype in both abiotic surfaces and lung epithelial cells. Also, the atsR mutant overexpressed and hypersecreted an Hcp-like protein known to be specifically secreted by the type VI secretion system (T6SS) in other gram-negative bacteria. Amoeba plaque assays demonstrated that the atsR mutant was more resistant to Dictyostelium predation than the wild-type strain and that this phenomenon was T6SS dependent. Macrophage infection assays also demonstrated that the atsR mutant induces the formation of actin-mediated protrusions from macrophages that require a functional Hcp-like protein, suggesting that the T6SS is involved in actin rearrangements. Three B. cenocepacia transposon mutants that were found in a previous study to be impaired for survival in chronic lung infection model were mapped to the T6SS gene cluster, indicating that the T6SS is required for infection in vivo. Together, our data show that AtsR is involved in the regulation of genes required for virulence in B. cenocepacia K56-2, including genes encoding a T6SS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".