In vivo expression technology identifies a type VI secretion system locus in Burkholderia pseudomallei that is induced upon invasion of macrophages
Bibliographic record
Abstract
The Gram-negative proteobacterium Burkholderia pseudomallei can survive and multiply within a variety of eukaryotic cells, including macrophages. This property is believed to be important for its ability to cause the disease melioidosis in a wide range of animal species, including humans. To identify determinants that are important for the ability of B. pseudomallei to survive within macrophages, in vivo expression technology (IVET) was employed. Several putative macrophage-inducible genes were identified that are likely to contribute to the virulence of B. pseudomallei, including three genes (tssH-5, tssI-5 and tssM-5) located within the same type VI secretion system cluster (tss-5), mntH, encoding a natural resistance-associated macrophage protein (NRAMP)-like manganese ion transporter, and a haem acquisition gene, bhuT. The macrophage-inducibility of the tss-5 gene cluster was confirmed by reporter gene analysis. Construction of tssH-5 and bhuT null mutants indicated that expression of the tss-5 unit and the bhu operon were not required for intramacrophage survival. A further five tss units were identified within the B. pseudomallei genome that, together with tss-5, account for approximately 2.3 % of the total genome size. The presence of six type VI secretion systems in this organism is likely to be an important factor in making this bacterium such a versatile pathogen.
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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) | 0.000 | 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".