Microbial Products Activate Monocytic Cells through Detergent-Resistant Membrane Microdomains
Bibliographic record
Abstract
Patients with cystic fibrosis suffer recurrent pulmonary infections that are characterized by an overactive yet ineffective and destructive inflammatory response that is associated with respiratory infections by Pseudomonas aeruginosa, a pathogen that produces a number of phlogistic molecules. To better understand this process, we used exoenzyme S (ExoS), one of the key P. aeruginosa-secreted exoproducts, which is known to stimulate cells via the Toll-like receptor (TLR) pathway. We found that ExoS induced proinflammatory cytokine production via the NF-kappaB, Erk1/2, and Src kinase pathways. Because Src kinases are concentrated within cholesterol-containing, detergent-resistant membrane microdomains (DRM) (also called lipid rafts) and DRM act as signaling platforms and amplifiers on the surface of cells, we addressed the role of DRM in ExoS signaling. ExoS bound directly to a subset of DRM and induced the phosphorylation of multiple proteins within DRM, including Src kinases. Disruption of DRM by cholesterol extraction prevented NF-kappaB and Erk 1/2 activation and TNF-alpha production in response to ExoS. Activation of monocytic cells by other TLR and Nod-like receptor agonists, such as lipoteichoic acid, lipopolysaccharide, and peptidoglycan, were also dependent on DRM, and disruption prevented TNF-alpha production. Disruption of DRM did not prevent ExoS binding but did release the Src kinase, Lyn, from the DRM fraction into the detergent-soluble fraction, a site in which Src kinases are not active. These studies show that ExoS, a TLR agonist, requires direct binding to DRM for optimal signaling, which suggests that DRM are possible therapeutic targets in cystic fibrosis.
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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".