Comparative genomics of <i>Campylobacter concisus</i> : Analysis of clinical strains reveals genome diversity and pathogenic potential
Bibliographic record
Abstract
In recent years, an increasing number of Campylobacter species have been associated with human gastrointestinal (GI) diseases including gastroenteritis, inflammatory bowel disease, and colorectal cancer. Campylobacter concisus, an oral commensal historically linked to gingivitis and periodontitis, has been increasingly detected in the lower GI tract. In the present study, we generated robust genome sequence data from C. concisus strains and undertook a comprehensive pangenome assessment to identify C. concisus virulence properties and to explain potential adaptations acquired while residing in specific ecological niche(s) of the GI tract. Genomes of 53 new C. concisus strains were sequenced, assembled, and annotated including 36 strains from gastroenteritis patients, 13 strains from Crohn's disease patients and four strains from colitis patients (three collagenous colitis and one lymphocytic colitis). When compared with previous published sequences, strains clustered into two main groups/genomospecies (GS) with phylogenetic clustering explained neither by disease phenotype nor sample location. Paired oral/faecal isolates, from the same patient, indicated that there are few genetic differences between oral and gut isolates which suggests that gut isolates most likely reflect oral strain relocation. Type IV and VI secretion systems genes, genes known to be important for pathogenicity in the Campylobacter genus, were present in the genomes assemblies, with 82% containing Type VI secretion system genes. Our findings indicate that C. concisus strains are genetically diverse, and the variability in bacterial secretion system content may play an important role in their virulence potential.
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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 | 0.001 |
| 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 | 0.001 | 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".