A nitric oxide-sensing two-component system regulates a range of infection-related phenotypes in <i>Burkholderia pseudomallei</i>
Bibliographic record
Abstract
ABSTRACT The tier 1 bioterrorism agent Burkholderia pseudomallei causes melioidosis, a tropical disease with fatality rates that can exceed 40% despite antibiotic therapy. Antibiotic failure is likely to be, at least in part, due to biofilm-dwelling B. pseudomallei, and therefore, an improved understanding of how this pathogen regulates biofilm formation could reveal new opportunities for clinical intervention. The antimicrobial radical nitric oxide (NO) plays a key role in host immune defenses against bacteria, and the ability of B. pseudomallei to sense and mitigate NO toxicity is vital for establishing infection. NO-sensing proteins (NosPs), which have recently emerged as key regulators of biofilm formation in many bacterial species, use a FIST domain to sense NO via a bound heme. We hypothesized that the NosP homolog in B. pseudomallei would regulate biofilm formation and mediate NO-protective responses. We used [γ- 32 P]ATP autophosphorylation assays to show that NosP of B. pseudomallei controls the autophosphorylation rate of an associated histidine kinase protein (NosK) in an NO-dependent manner. NosK was found to phosphorylate a response regulator protein (NosR) with an HD-GYP output domain, which is associated with c-di-GMP signaling, therefore implicating NosP in modulating c-di-GMP-regulated phenotypes. Unmarked, in-frame deletion of either nosP or nosK caused significant changes in B. pseudomallei biofilm formation and increased sensitivity to nitrosative stress, in addition to affecting other virulence traits such as growth and swimming motility. These results indicate that NosP and NosK signaling control a range of infection-relevant phenotypes and may serve as targets for novel therapeutic intervention. IMPORTANCE Melioidosis is an emerging, potentially life-threatening infection caused by the bacterium Burkholderia pseudomallei , killing ~89,000 people per year globally. Antibiotic therapy fails in ~10%–40% of cases, and hence, an improved understanding of the molecular mechanisms that control B. pseudomallei virulence could reveal new approaches for improving melioidosis treatment. Biofilm formation and resistance to the antimicrobial radical NO are virulence traits that help bacteria establish infections. Here, we show that two proteins in B. pseudomallei , NosP and NosK, work together to detect NO and regulate a suite of virulence traits, including NO resistance, biofilm formation, growth, and swimming motility. This work, therefore, improves our understanding of the molecular mechanisms that control infection-related phenotypes in B. pseudomallei .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".