Elucidating Global Epidemiology of <i>Burkholderia multivorans</i> in Cases of Cystic Fibrosis by Multilocus Sequence Typing
Bibliographic record
Abstract
Burkholderia multivorans is a prominent B. cepacia complex (BCC) species causing infection in people with cystic fibrosis. Despite infection control measures being introduced to reduce the spread of BCC there is a continued emergence of infections by B. multivorans. Our objective was to analyze a global collection of B. multivorans isolates, comparing those from environmental and clinical sources with those from reported outbreaks. Multilocus sequence typing (MLST) was performed on 107 B. multivorans isolates to provide a detailed analysis of the global population biology of this species. MLST resolved 64 B. multivorans sequence types. Twelve of these were globally distributed and associated with human infection; two of these (ST-21 and ST-375) were also composed of environmental isolates. These global lineages included strains previously linked to large outbreaks (e.g., French epidemic clone ST-16). Though few environmental isolates of B. multivorans were available for analysis, of six strains identified, three were identical to strains recovered from cystic fibrosis (CF) infection. Although the ability of B. multivorans to cause CF outbreaks is known, our report here concerning the existence of globally distributed B. multivorans CF strains is a new observation for this emerging B. cepacia complex pathogen and suggests that certain strain types may be better adapted to human infection than others. Common transmission-associated risk factors were not obviously linked to the globally distributed strains; however, the overlap in strains recovered from water environments, industrial products, and human infection suggests that environmental sources may be an important reservoir for infection with B. multivorans.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".