Distinguishing West Nile virus infection using a recombinant envelope protein with mutations in the conserved fusion-loop
Bibliographic record
Abstract
BACKGROUND: West Nile Virus (WNV) is an emerging mosquito-transmitted flavivirus that continues to spread and cause disease throughout several parts of the world, including Europe and the Americas. Specific diagnosis of WNV infections using current serological testing is complicated by the high degree of cross-reactivity between antibodies against other clinically relevant flaviviruses, including dengue, tick-borne encephalitis (TBEV), Japanese encephalitis (JEV), and yellow fever (YFV) viruses. Cross-reactivity is particularly problematic in areas where different flaviviruses co-circulate or in populations that have been immunized with vaccines against TBEV, JEV, or YFV. The majority of cross-reactive antibodies against the immunodominant flavivirus envelope (E) protein target a conserved epitope in the fusion loop at the distal end of domain II. METHODS: We tested a loss-of-function bacterially expressed recombinant WNV E protein containing mutations in the fusion loop and an adjacent loop domain as a possible diagnostic reagent. By comparing the binding of sera from humans infected with WNV or other flaviviruses to the wild type and the mutant E proteins, we analyzed the potential of this technology to specifically detect WNV antibodies. RESULTS: Using this system, we could reliably determine WNV infections. Antibodies from WNV-infected individuals bound equally well to the wild type and the mutant protein. In contrast, sera from persons infected with other flaviviruses showed significantly decreased binding to the mutant protein. By calculating the mean differences between antibody signals detected using the wild type and the mutant proteins, a value could be assigned for each of the flaviviruses, which distinguished their pattern of reactivity. CONCLUSIONS: Recombinant mutant E proteins can be used to discriminate infections with WNV from those with other flaviviruses. The data have important implications for the development of improved, specific serological assays for the detection of WNV antibodies in regions where other flaviviruses co-circulate or in populations that are immunized with other flavivirus vaccines.
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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 | 0.000 | 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 | 0.000 |
| 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".