Development of a Multiplex PCR Assay for Genotyping the Fish Pathogen Piscirickettsia salmonis Through Comparative Genomics
Bibliographic record
Abstract
Piscirickettsia salmonis is a bacterial pathogen that severely impact the aquaculture in several countries as Canada, Scotland, Ireland, Norway, and Chile. It provokes Piscirickettsiosis outbreaks in the marine phase of salmonid farming, resulting in economic losses. The monophyletic genogroup LF-89 and a divergent genogroup EM-90 are responsible for the most severe Piscirickettsiosis outbreaks in Chile. Therefore, the development of methods for quick genotyping of P. salmonis genogroups in field samples is vital for veterinary diagnoses and understanding the population structure of this pathogen. The present study reports the development of a multiplex PCR for genotyping LF-89 and EM-90 genogroups based on comparative genomics of 73 fully sequenced P. salmonis genomes. The results revealed 2,322 sequences shared between 35 LF-89 genomes, 2,280 sequences in the core-genome of 38 EM-90 genomes, and 331 and 534 accessory coding sequences each genogroup, respectively. A total of 1,801 clusters of coding sequences were shared among all tested genomes of P. salmonis (LF-89 and EM-90), with 253 and 291 unique sequences for LF-89 and EM-90 genogroups, respectively. The Multiplex-1 prototype was chosen for reliable genotyping because of differences in annealing temperatures and respective reaction efficiencies. This method also identified the pathogen in field samples infected with LF-89 or EM-90 strains, which is not possible with other methods currently available. Finally, the genome-based multiplex PCR protocol presented in this study is a rapid and affordable alternative to classical sequencing of PCR products and analyzing the length of restriction fragment polymorphisms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".