Competitive Growth Enhances Conditional Growth Mutant Sensitivity to Antibiotics and Exposes a Two-Component System as an Emerging Antibacterial Target in Burkholderia cenocepacia
Bibliographic record
Abstract
Chemogenetic approaches to profile an antibiotic mode of action are based on detecting differential sensitivities of engineered bacterial strains in which the antibacterial target (usually encoded by an essential gene) or an associated process is regulated. We previously developed an essential-gene knockdown mutant library in the multidrug-resistant Burkholderia cenocepacia by transposon delivery of a rhamnose-inducible promoter. In this work, we used Illumina sequencing of multiplex-PCR-amplified transposon junctions to track individual mutants during pooled growth in the presence of antibiotics. We found that competition from nontarget mutants magnified the hypersensitivity of a clone underexpressing gyrB to novobiocin by 8-fold compared with hypersensitivity measured during clonal growth. Additional profiling of various antibiotics against a pilot library representing most categories of essential genes revealed a two-component system with unknown function, which, upon depletion of the response regulator, sensitized B. cenocepacia to novobiocin, ciprofloxacin, tetracycline, chloramphenicol, kanamycin, meropenem, and carbonyl cyanide 3-chlorophenylhydrazone, but not to colistin, hydrogen peroxide, and dimethyl sulfoxide. We named the gene cluster esaSR for enhanced sensitivity to antibiotics sensor and response regulator. Mutational analysis and efflux activity assays revealed that while esaS is not essential and is involved in antibiotic-induced efflux, esaR is an essential gene and regulates efflux independently of antibiotic-mediated induction. Furthermore, microscopic analysis of cells stained with propidium iodide provided evidence that depletion of EsaR has a profound effect on the integrity of cell membranes. In summary, we unraveled a previously uncharacterized two-component system that can be targeted to reduce antibiotic resistance 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) | 0.001 | 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".