The lipid A palmitoyltransferase PagP: molecular mechanisms and role in bacterial pathogenesis
Bibliographic record
Abstract
Palmitoylated lipid A can both protect pathogenic bacteria from host immune defences and attenuate the activation of those same defences through the TLR4 signal transduction pathway. A palmitate chain from a phospholipid is incorporated into lipid A by an outer membrane enzyme PagP, which is an 8-stranded antiparallel beta-barrel preceded by an amino-terminal amphipathic alpha-helix. The PagP barrel axis is tilted by 25 degrees with respect to the membrane normal. An interior hydrophobic pocket in the outer leaflet-exposed half of the molecule functions as a hydrocarbon ruler that allows the enzyme to distinguish palmitate from other acyl chains found in phospholipids. Internalization of a phospholipid palmitoyl group within the barrel appears to occur by lateral diffusion from the outer leaflet through non-hydrogen-bonded regions between beta-strands. The MsbA-dependent trafficking of lipids from the inner membrane to the outer membrane outer leaflet is necessary for lipid A palmitoylation in vivo. The mechanisms by which bacteria regulate pagP gene expression strikingly reflect the corresponding pathogenic lifestyle of the bacterium. Variations on PagP structure and function can be illustrated with the known homologues from Gram-negative bacteria, which include pathogens of humans and other mammals in addition to pathogens of insects and plants. The PagP enzyme is potentially a target for the development of anti-infective agents, a probe of outer membrane lipid asymmetry, and a tool for the synthesis of lipid A-based vaccine adjuvants and endotoxin antagonists.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".