CHARACTERIZATION OF HaRNAV, A SINGLE‐STRANDED RNA VIRUS CAUSING LYSIS OF <i>HETEROSIGMA AKASHIWO</i> (RAPHIDOPHYCEAE)<sup>1</sup>
Bibliographic record
Abstract
HaRNAV, a novel virus that infects the toxic bloom‐forming alga Heterosigma akashiwo (Hada) Hada ex Hada et Chihara, was characterized based on morphology, pathology, nucleic acid type, structural proteins, and the range of host strains that it infects. HaRNAV is a 25‐nm single‐stranded RNA (ssRNA) virus with a genome size of approximately 9100 nucleotides. This is the first report of an ssRNA virus that causes lysis of a phytoplankton species. The virus particle is sensitive to chloroform and contains at least five structural proteins ranging in apparent size from 24 to 34 kDa. HaRNAV infection causes swelling of the endoplasmic reticulum and progeny virus particles assemble in the cytoplasm of the host, frequently in crystalline arrays. The infectivity of HaRNAV was tested against 15 strains of H. akashiwo isolated from Japanese waters, the Northeast Pacific, and the Northwest Atlantic. HaRNAV caused lysis of three strains from the Northeast Pacific and two strains from Japan but none from the Northwest Atlantic. The characterization of HaRNAV demonstrates that HaRNAV is a novel type of phytoplankton virus but has some similarities with plant viruses belonging to the Sequiviridae and to other known ssRNA viruses. Further genomic analysis, however, is necessary to determine any phylogenetic relationships. The discovery of HaRNAV emphasizes the diversity of H. akashiwo viral pathogens and, more importantly, algal–virus pathogens and the complexity of virus–host interactions in the environment.
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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 | 0.000 | 0.000 |
| 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".