Peptidoglycan-Modifying Enzyme Pgp1 Is Required for Helical Cell Shape and Pathogenicity Traits in Campylobacter jejuni
Bibliographic record
Abstract
The impact of bacterial morphology on virulence and transmission attributes of pathogens is poorly understood. The prevalent enteric pathogen Campylobacter jejuni displays a helical shape postulated as important for colonization and host interactions. However, this had not previously been demonstrated experimentally. C. jejuni is thus a good organism for exploring the role of factors modulating helical morphology on pathogenesis. We identified an uncharacterized gene, designated pgp1 (peptidoglycan peptidase 1), in a calcofluor white-based screen to explore cell envelope properties important for C. jejuni virulence and stress survival. Bioinformatics showed that Pgp1 is conserved primarily in curved and helical bacteria. Deletion of pgp1 resulted in a striking, rod-shaped morphology, making pgp1 the first C. jejuni gene shown to be involved in maintenance of C. jejuni cell shape. Pgp1 contributes to key pathogenic and cell envelope phenotypes. In comparison to wild type, the rod-shaped pgp1 mutant was deficient in chick colonization by over three orders of magnitude and elicited enhanced secretion of the chemokine IL-8 in epithelial cell infections. Both the pgp1 mutant and a pgp1 overexpressing strain - which similarly produced straight or kinked cells - exhibited biofilm and motility defects. Detailed peptidoglycan analyses via HPLC and mass spectrometry, as well as Pgp1 enzyme assays, confirmed Pgp1 as a novel peptidoglycan DL-carboxypeptidase cleaving monomeric tripeptides to dipeptides. Peptidoglycan from the pgp1 mutant activated the host cell receptor Nod1 to a greater extent than did that of wild type. This work provides the first link between a C. jejuni gene and morphology, peptidoglycan biosynthesis, and key host- and transmission-related characteristics.
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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 | 0.000 |
| 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".