Novel Divergent Members of the Kitrinoviricota Discovered through Metagenomics in the Intestinal Contents of Red-Backed Voles (Clethrionomys gapperi)
Bibliographic record
Abstract
Metagenomic methods are powerful tools to investigate viral diversity in biological or environmental samples and to identify previously unknown viruses. We used RNA metagenomics to identify, in the gut of red-backed voles, the nearly complete genomes of two novel members of the Kitrinoviricota, a phylum including viruses with positive-sense ssRNA genomes encoding an RNA-directed RNA polymerase. The genome of a novel member of the Tombusviridae presented four open reading frames (ORFs); a −1 frameshift is potentially involved in generating the viral replicase. This sequence was part of a phylogenetic clade that did not include any officially classified species. The second genome presented a large ORF coding for a viral polyprotein containing the typical protein domains common to flexiviruses. The sequence clustered with currently known members of the Deltaflexiviridae. Both viruses appear to represent the first members of novel species in yet undefined genera. The identified viruses likely originated from the vole diet as members of the two viral families are known to infect plants and fungi, respectively. Investigating public databases demonstrated that a much higher richness than currently recognized exists for these two viral families, highlighting the need to update taxonomy systems and possibly also include genomes identified through metagenomics.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".