The SPLUNC1-βENaC complex prevents Burkholderia cenocepacia invasion in normal airway epithelia
Bibliographic record
Abstract
Cystic fibrosis (CF) patients are extremely vulnerable to Burkholderia cepacia complex (Bcc) infections. However, the underlying etiology is poorly understood. We tested the hypothesis that short palate lung and nasal epithelial clone 1 (SPLUNC1)-epithelial sodium channel (ENaC) interactions at the plasma membrane are required to reduce Bcc burden in normal airways. To determine if SPLUNC1 was needed to reduce Bcc burden in the airways, SPLUNC1 knockout mice and their wild-type littermates were infected with B. cenocepacia strain J2315. SPLUNC1 knockout mice had increased bacterial burden in the lungs compared to wild-type littermate mice. SPLUNC1-knockdown primary human bronchial epithelia (HBECs) were incubated with J2315, which resulted in increased bacterial burden compared to non-transduced HBECs. We next determined the interaction of the SPLUNC1-ENaC complex during J2315 infection. SPLUNC1 remained at the apical plasma membrane of normal HBECs but less was present at the apical plasma membrane of CF HBECs. Additionally, SPLUNC1-βENaC complexes reduced intracellular J2315 burden. Our data indicate that (i) secreted SPLUNC1 is required to reduce J2315 burden in the airways and (ii) its interaction with ENaC prevents cellular invasion of J2315.
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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 | 0.001 |
| 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".