Use of PCRRFLP for genotyping 16S rRNA and characterizing bacteria cultured from halibut fry
Bibliographic record
Abstract
Small subunit ribosomal genes were explored using PCR-RFLP to facilitate the characterization of bacteria cultured from reared fry of the Atlantic halibut (Hippoglossus hippoglossus). Concern has been expressed about pathogen invasion in larvae lacking a counteracting normal flora that may aid the immune system in producing robust noninfected individuals. In this study, pure cultured representatives of normal flora that were previously found to be antagonistic towards a pathogenic Vibrio sp. were subjected to a whole cell PCR protocol amplifying approximately 1500 bp of 16S rDNA. Amplified DNA was digested by AluI, BstUI, CfoI, and RsaI, to generate restriction profiles. Before the isolates were characterized, a survey was performed to test the discriminative efficiency of the RFLP. Efficient detection of polymorphism and the resolution of species and subspecies were achieved. Using the RFLP on 103 isolates generated as many as 22 genotypes. Based on the restriction profiles, a taxonomic tree incorporating 19 reference strains was constructed. Partial sequencing found this tree to be dominated by gamma-Proteobacteria in clusters of Vibrio-, Pseudomonas-, and Alteromonas-affiliated species. Only nine isolates fell outside these genera, including the three isolates Shewanella alga, Deleya marina, and Marinomonas protea. These species have not previously been reported as halibut flora. The most frequently isolated genotype resembled Vibrio salmonicida.
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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) | 0.001 | 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 | 0.001 |
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".