The molecular determinants governing the immunogenicity of Japanese encephalitis live attenuated vaccines
Bibliographic record
Abstract
Abstract In the course of isolating the attenuated Japanese encephalitis vaccine SA14-14-2, two attenuated strains SA14-9-7 and SA14-5-3 were also obtained that elicited low antibody responses in humans (<10% and 62%, respectively) and exerted much weaker immune protection in animal challenge experiments. However, the reason for these differences remains unknown. In order to understand why SA14-14-2 is superior to SA14-9-7 and SA14-5-3, we employed a reverse genetics method to identify the key mutations in the virus genome that determine the immunogenicity of live attenuated Japanese encephalitis viruses. We first sequenced the full genomic sequences of SA14-9-7 and SA14-5-3 and found mutations that changed four amino-acid base pairs when compared to the envelope gene of SA14-14-2. We mutated the genome of SA14-14-2 to generate these mutations both singly (E-177, E-264, E-279 and E-315) and in combination (E-177/264, E-279/315 and E-177/264/279/315) and tested these mutants along with parental strains SA14-14-2, SA14-9-7 and SA14-5-3 for their immunogenicity in vivo. When mice were immunized with SA14-9-7 and SA14-5-3, lower levels of neutralizing antibodies were generated compared with the immune response to SA14-14-2. Furthermore, SA14-5-3 was more immunogenic than SA14-9-7, which replicated the results previously seen in humans. Point mutations E-177, E-264, E-279 and E-315 diminished the immunogenicity of SA14-14-2 with E-264 and E-315, contributing the most to this phenotype. The mutant rJEV (E-177/E-264/E-279/E-315) containing all four point mutations exhibited the lowest immunogenicity with a seroconversion rate of 0 at an inoculation dose of 103 PFU (plaque-forming unit). We have identified the key amino acids in the envelope protein that account for the superior immunogenicity of SA14-14-2.
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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) | 0.001 | 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".