Infection of Polarized Airway Epithelial Cells by Normal and Small-Colony Variant Strains of Staphylococcus aureus Is Increased in Cells with Abnormal Cystic Fibrosis Transmembrane Conductance Regulator Function and Is Influenced by NF-κB
Bibliographic record
Abstract
The infection of nonphagocytic host cells by Staphylococcus aureus and more particularly by small-colony variants (SCVs) may contribute to the persistence of this pathogen in the lungs of cystic fibrosis (CF) patients. The development of chronic infections is also thought to be facilitated by the proinflammatory status of CF airways induced by an activation of NF-κB. The aim of this study was to compare the infection of non-CF and CF-like airway epithelial cells by S. aureus strains (normal and SCVs) and to determine the impact of the interaction between cystic fibrosis transmembrane conductance regulator (CFTR) and NF-κB on the infection level of these cells by S. aureus. We developed an S. aureus infection model using polarized airway epithelial cells grown at the air-liquid interface and expressing short hairpin RNAs directed against CFTR to mimic the CF condition. A pair of genetically related CF coisolates with the normal and SCV phenotypes was characterized and used. Infection of both cell lines (non-CF and CF-like) was more productive with the SCV strain than with its normal counterpart. However, both normal and SCV strains infected more CF-like than non-CF cells. Accordingly, inhibition of CFTR function by CFTRinh-172 increased the S. aureus infection level. Experimental activation of NF-κB also increased the level of infection of polarized pulmonary epithelial cells by S. aureus, an event that could be associated with that observed when CFTR function is inhibited or impaired. This study supports the hypothesis that the proinflammatory status of CF tissues facilitates the infection of pulmonary epithelial cells by S. aureus.
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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) | 0.001 | 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".