Synthetic Cystic Fibrosis Sputum Medium Regulates Flagellar Biosynthesis through the flhF Gene in Burkholderia cenocepacia
Bibliographic record
Abstract
Burkholderia cenocepacia belongs to the Burkholderia cepacia complex (Bcc), a group of at least 18 distinct species that establish chronic infections in the lung of people with the genetic disease cystic fibrosis (CF). The sputum of CF patients is rich in amino acids and was previously shown to increase flagellar gene expression in B. cenocepacia. We examined flagellin expression and flagellar morphology of B. cenocepacia grown in synthetic cystic fibrosis sputum medium (SCFM) compared to minimal medium. We found that CF nutritional conditions induce increased motility and flagellin expression. Individual amino acids added at the same concentrations as found in SCFM also increased motility but not flagellin expression, suggesting a chemotactic effect of amino acids. Electron microscopy and flagella staining demonstrated that the increase in flagellin corresponds to a change in the number of flagella per cell. In minimal medium, the ratio of multiple: single: aflagellated cells was 2:3.5:4.5; while under SCFM conditions, the ratio was 7:2:1. We created a deletion mutant, ΔflhF, to study whether this putative GTPase regulates the flagellation pattern of B. cenocepacia K56-2 during growth in CF conditions. The ΔflhF mutant exhibited 80% aflagellated, 14% single and 6% multiple flagellated bacterial subpopulations. Moreover, the ratio of multiple to single flagella in WT and ΔflhF was 3.5 and 0.43, respectively in CF conditions. The observed differences suggest that FlhF positively regulates flagellin expression and the flagellation pattern in B. cenocepacia K56-2 during CF nutritional conditions.
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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".