Phylogenomic diversity of Vibrio species and other Gammaproteobacteria isolated from Pacific oysters (Crassostrea gigas) during a summer mortality outbreak
Why this work is in the frame
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Bibliographic record
Abstract
The Pacific oyster (PO), Crassostrea gigas , is an important commercial marine species but periodically experiences large stock losses due to disease events known as summer mortality. Summer mortality has been linked to environmental perturbations and numerous viral and bacterial agents, indicating this disease is multifactorial in nature. In 2013 and 2014, several summer mortality events occurred within the Port Stephens estuary (NSW, Australia). Extensive culture and molecular-based investigations were undertaken and several potentially pathogenic Vibrio species were identified. To improve species identification and genomically characterise isolates obtained from this outbreak, whole-genome sequencing (WGS) and subsequent genomic analyses were performed on 48 bacterial isolates, as well as a further nine isolates from other summer mortality studies using the same batch of juveniles. Average nucleotide identity (ANI) identified most isolates to the species level and included members of the Photobacterium , Pseudoalteromonas , Shewanella and Vibrio genera, with Vibrio species making up more than two-thirds of all species identified. Construction of a phylogenomic tree, ANI analysis, and pan-genome analysis of the 57 isolates represents the most comprehensive culture-based phylogenomic survey of Vibrios during a PO summer mortality event in Australian waters and revealed large genomic diversity in many of the identified species. Our analysis revealed limited and inconsistent associations between isolate species and their geographical origins, or host health status. Together with ANI and pan-genome results, these inconsistencies suggest that to determine the role that microbes may have in Pacific oyster summer mortality events, isolate identification must be at the taxonomic level of strain. Our WGS data (specifically, the accessory genomes) differentiated bacterial strains, and coupled with associated metadata, highlight the possibility of predicting a strain’s environmental niche and level of pathogenicity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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 it