Review: Lipopolysaccharide biosynthesis in <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Pseudomonas aeruginosa causes serious nosocomial infections, and an important virulence factor produced by this organism is lipopolysaccharide (LPS). This review summarizes knowledge about biosynthesis of all three structural domains of LPS - lipid A, core oligosaccharide, and O polysaccharides. In addition, based on similarities with other bacterial species, this review proposes new hypothetical pathways for unstudied steps in the biosynthesis of P. aeruginosa LPS. Lipid A biosynthesis is discussed in relation to Escherichia coli and Salmonella, and the biosyntheses of core sugar precursors and core oligosaccharide are summarised. Pseudomonas aeruginosa attaches a Common Polysaccharide Antigen and O-Specific Antigen polysaccharides to lipid A-core. Both forms of O polysaccharide are discussed with respect to their independent synthesis mechanisms. Recent advances in understanding O-polysaccharide biosynthesis since the last major review on this subject, published nearly a decade ago, are highlighted. Since P. aeruginosa O polysaccharides contain unusual sugars, sugar-nucleotide biosynthesis pathways are reviewed in detail. Knowledge derived from detailed studies in the O5, O6 and O11 serotypes is applied to predict biosynthesis pathways of sugars in poorly-studied serotypes, especially O1, O4, and O13/O14. Although further work is required, a full understanding of LPS biosynthesis in P. aeruginosa is almost within reach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".