NK Cells Play a Critical Protective Role in Host Defense against Acute Extracellular <i>Staphylococcus aureus</i> Bacterial Infection in the Lung
Bibliographic record
Abstract
Staphylococcus aureus remains a common cause of nosocomial bacterial infections and are often antibiotic resistant. The role of NK cells and IL-15 and their relationship in host defense against extracellular bacterial pathogens including S. aureus remain unclear. We have undertaken several approaches to address this issue using wild type (WT), IL-15 gene knock-out (KO), and NK cell-depleted mouse models. Upon pulmonary staphylococcal infection WT mice had markedly increased activated NK cells, but not NKT or gammadelta T cells, in the airway lumen that correlated with IL-15 production in the airway and with alveolar macrophages. In vitro exposure to staphylococcal products and/or coculture with lung macrophages directly activated NK cells. In contrast, lung macrophages better phagocytosed S. aureus in the presence of NK cells. In sharp contrast to WT controls, IL-15 KO mice deficient in NK cells were found to be highly susceptible to pulmonary staphylococcal infection despite markedly increased neutrophils and macrophages in the lung. In further support of these findings, WT mice depleted of NK cells were similarly susceptible to staphylococcal infection while they remained fully capable of IL-15 production in the lung at levels similar to those of NK-competent WT hosts. Our study thus identifies a critical role for NK cells in host defense against pulmonary extracellular bacterial infection and suggests that IL-15 is involved in this process via its indispensable effect on NK cells, but not other innate cells. These findings hold implication for the development of therapeutics in treating antibiotic-resistant S. aureus infection.
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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) | 0.002 | 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".