The<i>Burkholderia cepacia</i>Epidemic Strain Marker Is Part of a Novel Genomic Island Encoding Both Virulence and Metabolism-Associated Genes in<i>Burkholderia cenocepacia</i>
Bibliographic record
Abstract
The Burkholderia cepacia epidemic strain marker (BCESM) is a useful epidemiological marker for virulent B. cenocepacia strains that infect patients with cystic fibrosis. However, there was no evidence that the original marker, identified by random amplified polymorphic DNA fingerprinting, contributed to pathogenicity. Here we demonstrate that the BCESM is part of a novel genomic island encoding genes linked to both virulence and metabolism. The BCESM was present on a 31.7-kb low-GC-content island that encoded 35 predicted coding sequences (CDSs): an N-acyl homoserine lactone (AHL) synthase gene (cciI) and corresponding transcriptional regulator (cciR), representing the first time cell signaling genes have been found on a genomic island; fatty acid biosynthesis genes; an IS66 family transposase; transcriptional regulator CDSs; amino acid metabolism genes; and a group of hypothetical genes. Mutagenesis of the AHL synthase, amidase (amiI), and porin (opcI) genes on the island was carried out. Testing of the isogenic mutants in a rat model of chronic lung infection demonstrated that the amidase played a role in persistence, while the AHL synthase and porin were both involved in virulence. The island, designated the B. cenocepacia island (cci), is the first genomic island to be defined in the B. cepacia complex and its discovery validates the original epidemiological correlation of the BCESM with virulent CF strains. The features of the cci, which overlap both pathogenicity and metabolism, expand the concept of bacterial pathogenicity islands and illustrate the diversity of accessory functions that can be acquired by lateral gene transfer in bacteria.
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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".