Differences in both Toll-like receptor 4 and MD-2 account for the host-specific recognition of <i>Bordetella pertussis</i> lipid A (P1240)
Bibliographic record
Abstract
Abstract The lipid A portion of lipopolysaccharide (LPS) activates innate immunity through the Toll-like receptor 4 (TLR4)/MD-2 complex on host cells. Variation in lipid A has significant consequences for TLR4 activation and thus may be a means by which pathogenic bacteria modulate host immunity. We have previously seen that strain BP338 of Bordetella pertussis modifies its lipid A by the addition of glucosamine moieties which promote TLR4 activation in human macrophages. In the absence of glucosamine modification, TLR4 activation is attenuated. This effect is host-specific: glucosamine modification does not affect mouse TLR4 activation. We hypothesized that the species-specific effect is due to differences in TLR4, and used inter-species chimeric receptors to test this hypothesis. We found that the middle 330 amino acids of TLR4 were sufficient to generate species-specific responses to B. pertussis lipid A, dependent on co-expression of the matching species of MD-2. Based on the published crystal structure of TLR4/MD-2 in complex with E. coli LPS, we narrowed our search to the interface where TLR4/MD-2 complexes dimerize for activation, and used site-directed mutagenesis to identify specific amino acid residues in TLR4 and MD-2 that promote activation in response to B. pertussis lipid A. Taken together, we have demonstrated that charged amino acids in TLR4 and MD-2 contribute to host-specific immune responses to lipid A variants from B. pertussis.
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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 | 0.001 |
| 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) | 0.002 | 0.001 |
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".