Minor Modifications to the Phosphate Groups and the C3′ Acyl Chain Length of Lipid A in Two Bordetella pertussis Strains, BP338 and 18-323, Independently Affect Toll-like Receptor 4 Protein Activation
Bibliographic record
Abstract
Lipopolysaccharides (LPS) of Bordetella pertussis are important modulators of the immune system. Interaction of the lipid A region of LPS with the Toll-like receptor 4 (TLR4) complex causes dimerization of TLR4 and activation of downstream nuclear factor κB (NFκB), which can lead to inflammation. We have previously shown that two strains of B. pertussis, BP338 (a Tohama I-derivative) and 18-323, display two differences in lipid A structure. 1) BP338 can modify the 1- and 4'-phosphates by the addition of glucosamine (GlcN), whereas 18-323 cannot, and 2) the C3' acyl chain in BP338 is 14 carbons long, but only 10 or 12 carbons long in 18-323. In addition, BP338 lipid A can activate TLR4 to a greater extent than 18-323 lipid A. Here we set out to determine the genetic reasons for the differences in these lipid A structures and the contribution of each structural difference to the ability of lipid A to activate TLR4. We show that three genes of the lipid A GlcN modification (Lgm) locus, lgmA, lgmB, and lgmC (previously locus tags BP0399-BP0397), are required for GlcN modification and a single amino acid difference in LpxA is responsible for the difference in C3' acyl chain length. Furthermore, by introducing lipid A-modifying genes into 18-323 to generate isogenic strains with varying penta-acyl lipid A structures, we determined that both modifications increase TLR4 activation, although the GlcN modification plays a dominant role. These results shed light on how TLR4 may interact with penta-acyl lipid A species.
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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".