Accumulation of Peptidoglycan O-Acetylation Leads to Altered Cell Wall Biochemistry and Negatively Impacts Pathogenesis Factors of Campylobacter jejuni
Bibliographic record
Abstract
Campylobacter jejuni is a leading cause of bacterial gastroenteritis in the developed world. Despite its prevalence, its mechanisms of pathogenesis are poorly understood. Peptidoglycan (PG) is important for helical shape, colonization, and host-pathogen interactions in C. jejuni Therefore, changes in PG greatly impact the physiology of this organism. O-acetylation of peptidoglycan (OAP) is a bacterial phenomenon proposed to be important for proper cell growth, characterized by acetylation of the C6 hydroxyl group of N-acetylmuramic acid in the PG glycan backbone. The OAP gene cluster consists of a PG O-acetyltransferase A (patA) for translocation of acetate into the periplasm, a PG O-acetyltransferase B (patB) for O-acetylation, and an O-acetylpeptidoglycan esterase (ape1) for de-O-acetylation. In this study, reduced OAP in ΔpatA and ΔpatB had minimal impact on C. jejuni growth and fitness under the conditions tested. However, accumulation of OAP in Δape1 resulted in marked differences in PG biochemistry, including O-acetylation, anhydromuropeptide levels, and changes not expected to result directly from Ape1 activity. This suggests that OAP may be a form of substrate level regulation in PG biosynthesis. Ape1 acetylesterase activity was confirmed in vitro using p-nitrophenyl acetate and O-acetylated PG as substrates. In addition, Δape1 exhibited defects in pathogenesis-associated phenotypes, including cell shape, motility, biofilm formation, cell surface hydrophobicity, and sodium deoxycholate sensitivity. Δape1 was also impaired for chick colonization and adhesion, invasion, intracellular survival, and induction of IL-8 production in INT407 cells in vitro The importance of Ape1 in C. jejuni biology makes it a good candidate as an antimicrobial target.
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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".