A system for the construction of targeted unmarked gene deletions in the genus <i>Burkholderia</i>
Bibliographic record
Abstract
Burkholderia species are extremely multidrug resistant, environmental bacteria with extraordinary bioremediation and biocontrol properties. At the same time, these bacteria cause serious opportunistic infections in vulnerable patient populations while some species can potentially be used as bioweapons. The complete DNA sequence of more than 10 Burkholderia genomes provides an opportunity to apply functional genomics to a collection of widely adaptable environmental bacteria thriving in diverse niches and establishing both symbiotic and pathogenic associations with many different organisms. However, extreme multidrug resistance hampers genetic manipulations in Burkholderia. We have developed and evaluated a mutagenesis system based on the homing endonuclease I-SceI to construct targeted, non-polar unmarked gene deletions in Burkholderia. Using the cystic fibrosis pathogen Burkholderia cenocepacia K56-2 as a model strain, we demonstrate this system allows for clean deletions of one or more genes within an operon and also the introduction of multiple deletions in the same strain. We anticipate this tool will have widespread environmental and biomedical applications, facilitating functional genomic studies and construction of safe strains for bioremediation and biocontrol, as well as clinical applications such as live vaccines for Burkholderia and other Gram-negative bacterial species.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".