Antimicrobial peptide resistance mechanisms used by Enteropathogenic and Enterohemorrhagic «Escherichia coli»
Bibliographic record
Abstract
Enteropathogenic and enterohemorrhagic Escherichia coli (EPEC and EHEC) are Gram-negative pathogens that cause diarrheal disease in the developed and developing world. To cause infection, these pathogens must overcome innate host defenses, such as secreted cationic antimicrobial peptides (AMPs). There are two groups of human AMPs: cathelicidins (LL-37) and defensins (α-defensin 5). AMPs are expressed in specific locations of the human body. In the small intestine, the infectious niche for EPEC, human α-defensins 5 and 6 (HD-5 and HD-6) are abundant and there are low levels of LL-37. Conversely in the colon, the infectious niche for EHEC, HD-5 and HD-6 are not expressed and LL-37 is abundant. Pathogens can overcome AMP-killing using several mechanisms, including proteolytic inactivation, producing shielding structures and modifying their lipopolysaccharide (LPS). We hypothesized that EPEC and EHEC use AMP-resistance mechanisms to resist killing by secreted AMPs during infection. Previously, CroP the omptin protease in Citrobacter rodentium, a murine pathogen used to model EPEC and EHEC infections, was shown to degrade murine cathelicidin. Both EPEC and EHEC have a CroP-homologue: OmpT. The contribution of OmpT to LL-37 resistance was analyzed in both pathogens. Peptide cleavage assays showed that EHEC OmpT cleaves and inactivates LL-37 more rapidly than EPEC OmpT. Higher ompT-expression and protein levels in EHEC than EPEC are responsible for the differences observed in LL-37 inactivation rates. Additional studies showed that OmpT was unable to cleave folded α-defensins. These data suggest that EPEC uses other mechanisms to resist killing by the AMPs in its infectious niche. To assess this possibility, surface structures that may shield the bacterial membrane from AMPs were identified. High transcript levels of gfcA, a gene required for group 4 capsule (G4C) secretion, were observed in EPEC but not EHEC. The unencapsulated EPEC ΔgfcA and EHEC wild-type strains were more susceptible to HD-5 killing than EPEC wild-type. Since the G4C is composed of the same sugar repeats as the LPS O-antigen, an O-antigen ligase (waaL) deletion mutant was generated to assess the role of the O-antigen in HD-5 resistance. The EPEC ΔwaaL strain was more susceptible to HD-5 than both the wild-type and ΔgfcA strains. Addition of exogenous polysaccharide increased survival of the ΔgfcAΔwaaL strain in the presence of HD-5, suggesting that HD-5 binds the polysaccharides present on the surface of EPEC. These data show that EPEC relies on both the G4C and O-antigen to resist the bactericidal activity of HD-5. Altogether, these data indicate that EHEC and EPEC differentially regulate AMP-specific resistance mechanisms as an adaptation to their specific infectious niches.
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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".