Asian Zika virus can acquire generic African-lineage mutations during <i>in utero</i> infection
Bibliographic record
Abstract
The Zika virus 2015 epidemic showed an unusual phenotype for human flaviviruses, specifically fetal infection.We previously showed that in utero inoculation with the Asian Zika virus isolated from the human sample causes persistent infection in porcine fetuses.Here, we characterized the evolution of the Asian Zika virus in the fetal brain and placenta.Interestingly, the Asian Zika virus acquired generic African lineage K101R (A408G) and R1609 K (G4932A) mutations during in utero infection.Both African mutations were nonsynonymous and had a high frequency of nearly 100% in the fetal brain.Then, we synthetically generated the wild-type Asian variant and fetal brain-specific variant with generic African-lineage K101R and R1609 K mutations.In mosquito C6/36 cells, but not in human and pig cells, the fetal brain-specific variant showed higher virus loads compared to the Asian wild-type prototype.While in utero infection with both variants caused comparable virus loads in the placenta and amniotic fluids, fetuses injected with the fetal brain-specific variant had the trend to higher virus loads in lymph nodes.Also, introduced K101R and R1609 K mutations were stable and had high nearly 100% frequency at 28 days after in utero inoculation in both directly injected and trans-infected fetuses.These findings evoke concerns because Zika persists in pig herds and mosquitoes on farms in Mexico.It will be essential to identify how persistent in utero infection affects virus evolution and whether in utero-emerged Zika variants have the potential for shedding into the environment, more efficient transmission, and more aggressive infection phenotypes.
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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) | 0.003 | 0.001 |
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".