Inhibition of the type IV secretion system from antibiotic-resistant <i>Helicobacter pylori</i> clinical isolates supports the potential of Cagα as an anti-virulence target
Bibliographic record
Abstract
Helicobacter pylori resistance to antibiotics is a growing problem and it increasingly leads to treatment failure. While the bacterium is present worldwide, the severity of clinical outcomes is highly dependent on the geographical origin and genetic characteristics of the strains. One of the major virulence factors identified in H. pylori is the cag pathogenicity island ( cagPAI), which encodes a type IV secretion system (T4SS) used to translocate effectors into human cells. Here, we investigated the genetic variability of the cagPAI among 13 antibiotic-resistant H. pylori strains that were isolated from patient biopsies in Québec. Seven of the clinical strains carried the cagPAI, but only four could be readily cultivated under laboratory conditions. We observed variability of the sequences of CagA and CagL proteins that are encoded by the cagPAI. All clinical isolates induce interleukin-8 secretion and morphological changes upon co-incubation with gastric cancer cells and two of them produce extracellular T4SS pili. Finally, we demonstrate that molecule 1G2, a small molecule inhibitor of the Cagα protein from the model strain H. pylori 26695, reduces interleukin-8 secretion in one of the clinical isolates. Co-incubation with 1G2 also inhibits the assembly of T4SS pili, suggesting a mechanism for its action on T4SS function.
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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".