The unexpected discovery of a novel low-oxygen-activated locus for the anoxic persistence of <i>Burkholderia cenocepacia</i>
Bibliographic record
Abstract
Burkholderia cenocepacia is a Gram-negative aerobic bacterium that belongs to a group of opportunistic pathogens displaying diverse environmental and pathogenic lifestyles. B. cenocepacia is known for its ability to cause lung infections in people with cystic fibrosis and it possesses a large 8 Mb multireplicon genome encoding a wide array of pathogenicity and fitness genes. Transcriptomic profiling across nine growth conditions was performed to identify the global gene expression changes made when B. cenocepacia changes niches from an environmental lifestyle to infection. In comparison to exponential growth, the results demonstrated that B. cenocepacia changes expression of over one-quarter of its genome during conditions of growth arrest, stationary phase and surprisingly, under reduced oxygen concentrations (6% instead of 20.9% normal atmospheric conditions). Multiple virulence factors are upregulated during these growth arrest conditions. A unique discovery from the comparative expression analysis was the identification of a distinct, co-regulated 50-gene cluster that was significantly upregulated during growth under low oxygen conditions. This gene cluster was designated the low-oxygen-activated (lxa) locus and encodes six universal stress proteins and proteins predicted to be involved in metabolism, transport, electron transfer and regulation. Deletion of the lxa locus resulted in B. cenocepacia mutants with aerobic growth deficiencies in minimal medium and compromised viability after prolonged incubation in the absence of oxygen. In summary, transcriptomic profiling of B. cenocepacia revealed an unexpected ability of aerobic Burkholderia to persist in the absence of oxygen and identified the novel lxa locus as key determinant of this important ecophysiological trait.
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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 | 0.001 |
| 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 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".