Deep-sequencing of Marburg virus genome during sequential mouse passaging and cell-culture adaptation reveals extensive changes over time
Bibliographic record
Abstract
Marburg virus (MARV) has caused outbreaks of filoviral hemorrhagic fever since its discovery in 1967. The largest and deadliest outbreak occurred in Angola in 2005, with 252 cases and 227 deaths. In 2014, we developed a mouse-adapted MARV, Angola variant through serial passaging in mice. The mouse-adapted MARV exhibits many of the hallmarks of MARV disease in humans. By applying deep-sequencing to every passage of the virus, we are able to study virus evolution in this host with surprising precision. We show that two regions go through substantial changes: the intergenic region between NP and VP35, as well as the first 100 amino acids of the VP40 protein. Our results also reveal that there were profound changes during the production of the final virus stock in cell culture. Overall, our results show that a handful of regions carry most of the mutations acquired during the adaptation of the virus to a new host and that many mutations become fixed very early during the adaptation process.
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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 | 0.001 |
| 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 | 0.001 |
| 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".