Genomic population structure of Helicobacter pylori Shanghai isolates and identification of genomic features uniquely linked with pathogenicity
Bibliographic record
Abstract
Severe Helicobacter pylori-linked gastric disorders are especially prevalent in the East Asia region. The ability of H. pylori to cause different clinical outcomes is thought to be associated with unique sets of its genetic features. However, only few genetic features have been definitively linked to specific gastrointestinal pathologies. Genome heterogeneity of clinical H. pylori strains from patients with four different gastric disorders was studied to explore the population structure and molecular genomic features and their association with pathogenicity. Population analysis showed that 92.9% of the Shanghai H. pylori isolates were clustered in the East Asia group. Among 2,866 genes detected in all genomes, 1,146 genes formed the core genome, whereas 209 unique genes were detected in individual disease groups. The unique genes of peptic ulcer and gastric cancer groups represented the inorganic ion transport and metabolism function gene clusters. Sixteen virulence genes were detected with statistically different detection rates among the four disease groups. Furthermore, 127 clustered regularly interspaced short palindromic repeats were found with significantly different rates in the four disease groups. A total of 337 putative genomic islands were identified, and three genomic islands were individually found in more than 10% of strains. The genomic islands included several metabolism-associated genes and many genes with unknown function. In total, 88 sequence types were detected among the 112 Shanghai H. pylori isolates. Our study provides an essential milestone in the mapping of specific genomic features and their functions to identify factors needed to induce specific gastric disorders in H. pylori.
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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 | 0.001 | 0.001 |
| 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".