Evaluation of the Genetic Differences Between Two Subtypes of Campylobacter fetus (Fetus and Venerealis) in Canada
Bibliographic record
Abstract
The pathogen Campylobacter fetus (CF) is classified into two subspecies, Campylobacter fetus subspecies fetus (CFF) and Campylobacter fetus subspecies venerealis (CFV). Even though CFF and CFV are genetically closely related, they exhibit differences in their host adaptation; CFF inhabits the gastrointestinal tract of both humans and several animal species, while classical CFV is specific to the bovine genital tract and is of particular concern with respect to international bovine trade regulation. Traditionally, differentiation between the two subspecies has been achieved using a limited number of biochemical tests but more rapid and definitive genetic methods of discrimination are desired. A recent study suggested that the presence of a genomic island only in CFV could discriminate between the two sub- species but this hypothesis could not be confirmed on a collection of isolates originating in Canada. To identify alternative gene targets that would support accurate subspecies discrimination, this study has applied several approaches including suppression subtractive hybridization and whole genome sequencing supplemented with optical mapping. A subtractive hybridization screen, using a well-characterized CFV isolate recovered during routine screening of bulls in an Artificial Insemination center in western Canada and that lacked much of the genomic island and a typical Canadian CFF isolate, yielded 50 clones; characterization of these clones by hybridization screening against selected CF isolates and by nucleotide sequence BLAST analysis identified three potentially CFV-specific clones that contained inserts originating from a second genomic island. Further screening using a larger CF sample set found that only Clone #35 was truly CFV-specific. Optical maps (NcoI digest) of the Canadian CFF and CFV isolates used for the subtractive hybridization showed that certain regions of these genomes were quite distinct from those of two reference strains. Whole genome sequencing of these two isolates identified two target genes (PICFV5_ORF548 and CFF_Feature #3) that appear to be selectively retained in the two subspecies. Screening of a collection of CF isolates by PCRs targeting these three loci (SSH_Clone #35, PICFV5_ORF548 and CFF_Feature #3) supported their use for subspecies discrimination. This work demonstrates the complex genomic diversity associated with these CF subtypes and the challenge posed by their discrimination using limited genetic loci.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".