Development of a Multiple-Locus Variable-Number Tandem-Repeat Typing Scheme for Genetic Fingerprinting of Burkholderia cenocepacia and Application to Nationwide Epidemiological Analysis
Bibliographic record
Abstract
Organisms of the Burkholderia cepacia complex are especially important pathogens in cystic fibrosis (CF), with a propensity for patient-to-patient spread and long-term respiratory colonization. B. cenocepacia and Burkholderia multivorans account for the majority of infections in CF, and major epidemic clones have been recognized throughout the world. The aim of the present study was to develop and evaluate a multilocus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for B. cenocepacia. Potential VNTR loci were identified upon analysis of the annotated genome sequences of B. cenocepacia strains AU1054, J2315, and MCO-3, and 10 of them were selected on the basis of polymorphisms and size. A collection of 100 B. cenocepacia strains, including epidemiologically related and unrelated strains, as well as representatives of the major epidemic lineages, was used to evaluate typeability, epidemiological concordance, and the discriminatory power of MLVA-10 compared with those of pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Longitudinal stability was assessed by testing 39 successive isolates from 14 patients. Typeability ranged from 0.91 to 1, except for that of one marker, which was not amplified in 53% of the B. cenocepacia IIIA strains. The MLVA types were shown to be stable in chronically colonized patients and within outbreak-related strains, with excellent epidemiological concordance. Epidemic and/or globally distributed lineages (epidemic Edinburgh-Toronto electrophoretic type 12 [ET-12], sequence type 32 [ST-32], ST-122, ST-234, and ST-241) were successfully identified. Conversely, the discriminatory power of MLVA was lower than that of PFGE or MLST, although PFGE variations within the epidemic lineages sometimes masked their genetic relatedness. In conclusion, MLVA represents a promising cost-effective first-line tool in B. cenocepacia surveillance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| 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) | 0.000 | 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".