Multiple Acid Sensors Control Helicobacter pylori Colonization of the Stomach
Bibliographic record
Abstract
Helicobacter pylori's ability to respond to environmental cues in the stomach is integral to its survival. By directly visualizing H. pylori swimming behavior when encountering a microscopic gradient consisting of the repellent acid and attractant urea, we found that H. pylori is able to simultaneously detect both signals, and its response depends on the magnitudes of the individual signals. By testing for the bacteria's response to a pure acid gradient, we discovered that the chemoreceptors TlpA and TlpD are each independent acid sensors. They enable H. pylori to respond to and escape from increases in hydrogen ion concentration near 100 nanomolar. TlpD also mediates attraction to basic pH, a response dampened by another chemoreceptor TlpB. H. pylori mutants lacking both TlpA and TlpD (ΔtlpAD) are unable to sense acid and are defective in establishing colonization in the murine stomach. However, blocking acid production in the stomach with omeprazole rescues ΔtlpAD's colonization defect. We used 3D confocal microscopy to determine how acid blockade affects the distribution of H. pylori in the stomach. We found that stomach acid controls not only the overall bacterial density, but also the microscopic distribution of bacteria that colonize the epithelium deep in the gastric glands. In omeprazole treated animals, bacterial abundance is increased in the antral glands, and gland colonization range is extended to the corpus. Our findings indicate that H. pylori has evolved at least two independent receptors capable of detecting acid gradients, allowing not only survival in the stomach, but also controlling the interaction of the bacteria with the epithelium.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".