Novel, Divergent Simian Hemorrhagic Fever Viruses in a Wild Ugandan Red Colobus Monkey Discovered Using Direct Pyrosequencing
Bibliographic record
Abstract
BACKGROUND: Simian hemorrhagic fever virus (SHFV) has caused lethal outbreaks of hemorrhagic disease in captive primates, but its distribution in wild primates has remained obscure. Here, we describe the discovery and genetic characterization by direct pyrosequencing of two novel, divergent SHFV variants co-infecting a single male red colobus monkey from Kibale National Park, Uganda. METHODOLOGY/PRINCIPAL FINDINGS: The viruses were detected directly from blood plasma using pyrosequencing, without prior virus isolation and with minimal PCR amplification. The two new SHFV variants, SHFV-krc1 and SHFV-krc2 are highly divergent from each other (51.9% nucleotide sequence identity) and from the SHFV type strain LVR 42-0/M6941 (52.0% and 51.8% nucleotide sequence identity, respectively) and demonstrate greater phylogenetic diversity within SHFV than has been documented within any other arterivirus. Both new variants nevertheless have the same 3' genomic architecture as the type strain, containing three open reading frames not present in the other arteriviruses. CONCLUSIONS/SIGNIFICANCE: These results represent the first documentation of SHFV in a wild primate and confirm the unusual 3' genetic architecture of SHFV relative to the other arteriviruses. They also demonstrate a degree of evolutionary divergence within SHFV that is roughly equivalent to the degree of divergence between other arterivirus species. The presence of two such highly divergent SHFV variants co-infecting a single individual represents a degree of within-host viral diversity that exceeds what has previously been reported for any arterivirus. These results expand our knowledge of the natural history and diversity of the arteriviruses and underscore the importance of wild primates as reservoirs for novel pathogens.
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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".