Comparative Genomics of Typical and Atypical Aeromonas salmonicida Complete Genomes Revealed New Insights into Pathogenesis Evolution
Bibliographic record
Abstract
Aeromonas salmonicida is a global distributed Gram-negative teleost pathogen, affecting mainly salmonids in fresh and marine environments. A. salmonicida strains are classified as typical or atypical depending on their origin of isolation and phenotype. Five subspecies have been described, where A. salmonicida subsp. salmonicida is the only typical subspecies, and the subsp. achromogenes, masoucida, smithia, and pectinolytica are considered atypical. Genomic differences between A. salmonicida subsp. salmonicida isolates and their relationship with the current classification have not been explored. Here, we sequenced and compared the complete closed genomes of four virulent strains to elucidate their molecular diversity and pathogenic evolution using the more accurate genomic information so far. Phenotypes, biochemical, and enzymatic profiles were determined. PacBio and MiSeq sequencing platforms were utilized for genome sequencing. Comparative genomics showed that atypical strains belong to the subsp. salmonicida, with 99.55% ± 0.25% identity with each other, and are closely related to typical strains. The typical strain A. salmonicida J223 is closely related to typical strains, with 99.17% identity with the A. salmonicida A449. Genomic differences between atypical and typical strains are strictly related to insertion sequences (ISs) activity. The absence and presence of genes encoding for virulence factors, transcriptional regulators, and non-coding RNAs are the most significant differences between typical and atypical strains that affect their phenotypes. Plasmidome plays an important role in A. salmonicida virulence and genome plasticity. Here, we determined that typical strains harbor a larger number of plasmids and virulence-related genes that contribute to its acute virulence. In contrast, atypical strains harbor a single, large plasmid and a smaller number of virulence genes, reflected by their less acute virulence and chronic infection. The relationship between phenotype and A. salmonicida subspecies’ taxonomy is not evident. Comparative genomic analysis based on completed genomes revealed that the subspecies classification is more of a reflection of the ecological niche occupied by bacteria than their divergences at the genomic level except for their accessory genome.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".