Stable and assayable polymicrobial human airway model reveals complex interactions between <i>Pseudomonas aeruginosa</i> and lung commensals
Bibliographic record
Abstract
Abstract Polymicrobial-host crosstalk shapes airway barrier integrity and inflammation, yet standard in vitro systems rarely sustain interaction-dependent phenotypes. We engineered an aqueous two-phase system (ATPS) confined bronchial co-culture that stabilized day-scale assays while maintaining epithelial function. A 16HBE14o-/HUVEC cell insert model was challenged with Pseudomonas aeruginosa PA01, Streptococcus pneumoniae D39, and the commensals Rothia mucilaginosa and Lactobacillus casei in mono- and polymicrobial combinations. We evaluated epithelium permeability to FITC-dextran, cell junction integrity, bacterial-induced cytotoxicity, IL-6 and IL-8 release and bacterial viability. ATPS preserved a workable assay window and bacterial confinement over 24h. PA01 disrupted barrier integrity, and commensals mitigated this pathogenic effect, whereas PA01 co-cultured with S. pneumoniae exhibited synergistic damage effects on the lung epithelium. Junctional imaging corroborated functional readouts, and cytotoxicity remained low across conditions. Cytokine shifts were condition-specific but modest, demonstrating compatibility for soluble mediator profiling. We generated a human airway-microbiome model in which ATPS confinement enabled modelling of dynamic lung-microbiome interactions, reproducing known P. aeruginosa pathogenic effects and commensal protection of the epithelium.
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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 | 0.000 |
| 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".