Genomic diversity and evolutionary patterns of Edwardsiella ictaluri affecting farmed striped catfish (Pangasianodon hypophthalmus) in Vietnam over 20 years
Bibliographic record
Abstract
Edwardsiella ictaluri continues to pose a significant risk to the health and production of striped catfish ( Pangasianodon hypophthalmus ) in Vietnam. Whilst recent advances in genomic sequencing provide an insight into the global genomic diversity of this important fish pathogen, genome-wide analysis of Vietnamese isolates recovered over time is lacking. In this study, we used a whole-genome sequencing approach to compare the genomes of 31 E. ictaluri isolates recovered over a 20-year period (2001–2021) and performed comparative genomic analysis to explore temporal changes in genome diversity, population structure and mechanisms driving pathogenesis and antimicrobial resistance. Our findings revealed an open pan-genome with 4148 genes and a core genome (3 060 genes) accounting for over two-thirds of the genome. Moreover, we found the genomes sequenced to classify into two distinct lineages and estimated the ancestral origin of these lineages within Vietnam to date back to the 1950s. Plasmids were highly prevalent in Vietnamese E. ictaluri , with isolates harbouring up to four plasmids within their genome. Further, a diverse mobilome was observed with nine different plasmid types detected across the genome collection. Exploration of putative plasmids revealed a diverse set of antimicrobial resistance genes (ARGs) against key antibiotics used in Vietnamese aquaculture and virulence genes associated with protein secretion systems. Correlation analysis revealed the total number of ARGs detected in genomes to increase with isolate recovery time. Whilst the number of virulence genes remained relatively stable, temporal variation was noted in several virulence factors related to motility and immune system modulation. Findings from this study highlight the need for continued genomic surveillance to monitor changes in antimicrobial resistance and pathogenesis, to help inform the development of disease control and management strategies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".