Peptidoglycan ld-Carboxypeptidase Pgp2 Influences Campylobacter jejuni Helical Cell Shape and Pathogenic Properties and Provides the Substrate for the dl-Carboxypeptidase Pgp1
Bibliographic record
Abstract
Despite the importance of Campylobacter jejuni as a pathogen, little is known about the fundamental aspects of its peptidoglycan (PG) structure and factors modulating its helical morphology. A PG dl-carboxypeptidase Pgp1 essential for maintenance of C. jejuni helical shape was recently identified. Bioinformatic analysis revealed the CJJ81176_0915 gene product as co-occurring with Pgp1 in several organisms. Deletion of cjj81176_0915 (renamed pgp2) resulted in straight morphology, representing the second C. jejuni gene affecting cell shape. The PG structure of a Δpgp2 mutant showed an increase in tetrapeptide-containing muropeptides and a complete absence of tripeptides, consistent with ld-carboxypeptidase activity, which was confirmed biochemically. PG analysis of a Δpgp1Δpgp2 double mutant demonstrated that Pgp2 activity is required to generate the tripeptide substrate for Pgp1. Loss of pgp2 affected several pathogenic properties; the deletion strain was defective for motility in semisolid agar, biofilm formation, and fluorescence on calcofluor white. Δpgp2 PG also caused decreased stimulation of the human nucleotide-binding oligomerization domain 1 (Nod1) proinflammatory mediator in comparison with wild type, as expected from the reduction in muropeptide tripeptides (the primary Nod1 agonist) in the mutant; however, these changes did not alter the ability of the Δpgp2 mutant strain to survive within human epithelial cells or to elicit secretion of IL-8 from epithelial cells after infection. The pgp2 mutant also showed significantly reduced fitness in a chick colonization model. Collectively, these analyses enhance our understanding of C. jejuni PG maturation and help to clarify how PG structure and cell shape impact pathogenic attributes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".