Flagellar Hooks and Hook Protein FlgE Participate in Host Microbe Interactions at Immunological Level
Bibliographic record
Abstract
Host-microbe interactions determine the outcome of host responses to commensal and pathogenic microbes. Previously, two epithelial cell-binding peptides were found to be homologues of two sites (B, aa168-174; F, aa303-309) in the flagellar hook protein FlgE of Pseudomonas aeruginosa. Tertiary modeling predicted these sites at the interface of neighboring FlgE monomers in the fully formed hook. Recombinant FlgE protein stimulated proinflammatory cytokine production in a human cell line and in murine lung organoid culture as detected with real-time RT-PCR and ELISA assays. When administered to mice, FlgE induced lung inflammation and enhanced the Th2-biased humoral response to ovalbumin. A pull-down assay performed with FlgE-saturated resin identified caveolin-1 as an FlgE-binding protein, and caveolin-1 deficiency impaired FlgE-induced inflammation and downstream Erk1/2 pathway activation in lung organoids. Intact flagellar hooks from bacteria were also proinflammatory. Mutations to sites B and F impaired bacteria motility and proinflammatory potency of FlgE without altering adjuvanticity of FlgE. These findings suggest that the flagellar hook and FlgE are novel players in host-bacterial interactions at immunological level. Further studies along this direction would provide new opportunities for understanding and management of diseases related with bacterial 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) | 0.001 | 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".