Emergence of Viral hemorrhagic septicemia virus in the North American Great Lakes region is associated with low viral genetic diversity
Bibliographic record
Abstract
Viral hemorrhagic septicemia virus (VHSV) is a fish rhabdovirus that causes disease in a broad range of marine and freshwater hosts. The known geographic range includes the Northern Atlantic and Pacific Oceans, and recently it has invaded the Great Lakes region of North America. The goal of this work was to characterize genetic diversity of Great Lakes VHSV isolates at the early stage of this viral emergence by comparing a partial glycoprotein (G) gene sequence (669 nt) of 108 isolates collected from 2003 to 2009 from 31 species and at 37 sites. Phylogenetic analysis showed that all isolates fell into sub-lineage IVb within the major VHSV genetic group IV. Among these 108 isolates, genetic diversity was low, with a maximum of 1.05% within the 669 nt region. There were 11 unique sequences, designated vcG001 to vcG011. Two dominant sequence types, vcG001 and vcG002, accounted for 90% (97 of 108) of the isolates. The vcG001 isolates were most widespread. We saw no apparent association of sequence type with host or year of isolation, but we did note a spatial pattern, in which vcG002 isolates were more prevalent in the easternmost sub-regions, including inland New York state and the St. Lawrence Seaway. Different sequence types were found among isolates from single disease outbreaks, and mixtures of types were evident within 2 isolates from individual fish. Overall, the genetic diversity of VHSV in the Great Lakes region was found to be extremely low, consistent with an introduction of a new virus into a geographic region with previously naive host populations.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".