Postnatal Identification of Zika Virus Peptides from Saliva
Bibliographic record
Abstract
We explored the potential to diagnose Zika virus (ZIKV) infection by analyzing peptides in saliva during a convalescent phase of infection, long after resolution of acute disease. A 25-y-old woman clinically diagnosed with Zika fever in the first trimester was enrolled with her dizygotic twins for a 3-mo postnatal sample of saliva (9-mo after maternal infection). The female baby (A) had microcephaly while the male baby (B) was born healthy. Peptidomic analysis was completed by mass spectrometry (MS/MS), and ZIKV peptides were identified using the National Institutes of Health Zika Virus Resource database, then aligned and mapped to the ZIKV polyprotein to determine proteome coverage and phylogenetic studies. A total of 423 (mother), 607 (baby A), and 183 (baby B) unique ZIKV peptides were identified in saliva by MS/MS, providing a coverage of 67%, 84%, and 45%, respectively, of the entire ZIKV polyprotein (>3,400 amino acids). All peptides were aligned to other flaviviruses that are circulating in Brazil (dengue and yellow fever) to discard false-positive matches. Nine peptides identified were highly conserved to dengue virus. Alignment of a contiguous peptide sequence for mother/babies with the 74 ZIKV sequences suggested that the virus may have entered the oral cavity through the salivary glands, leading to an infection that persists into the postnatal period (vertical transmission). Furthermore, we identified 9 sequence variations that were unique to the baby with microcephaly (not found in the mother or the twin). This sequence information could provide a template for future neuropathogenic studies. A much larger sample size is required to determine whether sequence variation in the envelope protein significantly associates with microcephaly. Finally, from a public health perspective, it will be important to determine whether viral replication is still taking place after birth and whether the virus can be transmitted through salivary contact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".