Chromosomal<i>gfp</i>labelling of<i>Pseudomonas aeruginosa</i>using a mini-Tn<i>7</i>transposon: application for studies of bacteria–host interactions
Bibliographic record
Abstract
Analysis of bacterial interactions with host cells using multiple techniques is essential for studies on microbial pathogenesis and for the development of new antimicrobial therapies. Pseudomonas aeruginosa is an important opportunistic pathogen that can cause severe, often life-threatening pulmonary infections in individuals with impaired host defense mechanisms. Using a mini-Tn7 transposon delivery system, we have chromosomally labelled the strain P. aeruginosa PAK with a green fluorescent protein gene (gfp) and tested PAKgfp as a research tool for studies of bacteria-host interactions. We were able to reliably and rapidly measure the interactions of PAKgfp with A549 human lung epithelial cells by using flow cytometry, a fluorometric microplate reader-based assay, and fluorescence microscopy. With these analytical tools, we have demonstrated the adhesion of PAKgfp to the extracellular matrix protein fibronectin and the involvement of fibronectin in PAKgfp-A549 cell interactions. PAKgfp can be successfully used to explore the effects of various pharmacological compounds on P. aeruginosa - host cell interactions in both in vitro and in vivo systems, with potentially important medical applications.
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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 | 0.001 | 0.001 |
| 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".