A Genomic Survey of Positive Selection in Burkholderia pseudomallei Provides Insights into the Evolution of Accidental Virulence
Bibliographic record
Abstract
Certain environmental microorganisms can cause severe human infections, even in the absence of an obvious requirement for transition through an animal host for replication ("accidental virulence"). To understand this process, we compared eleven isolate genomes of Burkholderia pseudomallei (Bp), a tropical soil microbe and causative agent of the human and animal disease melioidosis. We found evidence for the existence of several new genes in the Bp reference genome, identifying 282 novel genes supported by at least two independent lines of supporting evidence (mRNA transcripts, database homologs, and presence of ribosomal binding sites) and 81 novel genes supported by all three lines. Within the Bp core genome, 211 genes exhibited significant levels of positive selection (4.5%), distributed across many cellular pathways including carbohydrate and secondary metabolism. Functional experiments revealed that certain positively selected genes might enhance mammalian virulence by interacting with host cellular pathways or utilizing host nutrients. Evolutionary modifications improving Bp environmental fitness may thus have indirectly facilitated the ability of Bp to colonize and survive in mammalian hosts. These findings improve our understanding of the pathogenesis of melioidosis, and establish Bp as a model system for studying the genetics of accidental virulence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".