Genetic import and phenotype specific alleles associated with hyper-invasion in Campylobacter jejuni
Bibliographic record
Abstract
BACKGROUND: Campylobacter jejuni is a major zoonotic pathogen, causing gastroenteritis in humans. Invasion is an important pathogenesis trait by which C. jejuni causes disease. Here we report the genomic analysis of 134 strains to identify traits unique to hyperinvasive isolates. METHODS: A total of 134 C. jejuni genomes were used to create a phylogenetic tree to position the hyperinvasive strains. Comparative genomics lead to the identification of mosaic capsule regions. A pan genome approach led to the discovery of unique loci, or loci with unique alleles, to the hyperinvasive strains. RESULTS: Phylogenetic analysis showed that the hyper-invasive phenotype is a generalist trait. Despite the fact that hyperinvasive strains are only distantly related based on the whole genome phylogeny, they all possess genes within the capsule region with high identity to capsule genes from C. jejuni subsp. doylei and C. lari. In addition there were genes unique to the hyper-invasive strains with identity to non-C. jejuni genes, as well as allelic variants of mainly pathogenesis related genes already known in the other C. jejuni. In particular, the sequence of flagella genes, flgD-E and flgL were highly conserved amongst the hyper-invasive strains and divergent from sequences in other C. jejuni. A novel cytolethal distending toxin (cdt) operon was also identified as present in all hyper-invasive strains in addition to the classic cdt operon present in other C. jejuni. CONCLUSIONS: Overall, the hyper-invasive phenotype is strongly linked to the presence of orthologous genes from other Campylobacter species in their genomes, notably within the capsule region, in addition to the observed association with unique allelic variants in flagellar genes and the secondary cdt operon which is unlikely under random sharing of accessory alleles in separate lineages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".