Plant production of a virus-like particle-based vaccine candidate against porcine reproductive and respiratory syndrome
Bibliographic record
Abstract
Porcine reproductive and respiratory syndrome (PRRS) is a disease leading to spontaneous abortions and stillbirths in sows and lowered life quality and expectancy in growing pigs. PRRS is prevalent worldwide and has significant economic impacts to swine industries around the globe. Co-expression of the two most abundant proteins in the viral envelope, the matrix protein (M) and glycosylated protein 5 (GP5), can produce a neutralizing immune response for the virus providing a potentially effective subunit vaccine against the disease, but these proteins are difficult to express. The goal of this research was to display antigenic portions of the M and GP5 proteins on the surface of tobacco mosaic virus-like particles. A modified tobacco mosaic virus coat protein (TMVc) was transiently expressed in Nicotiana benthamiana leaves and targeted to three subcellular compartments along the secretory pathway to introduce glycosylation patterns important for M-GP5 epitope immunogenicity. We found that accumulation levels in the apoplast were similar to the ER and the vacuole. Because glycans present on plant apoplastic proteins are closest to those present on PRRSV proteins, a TMVc-M-GP5 fusion construct was targeted to the apoplast and accumulated at over 0.5 mg/g of plant fresh weight. TMVc virus-like particles self-assembled in plant cells and surface-displayed the M-GP5 epitope, as visualized by transmission electron microscopy and immunogold localization. These promising findings lay the foundation for immunogenicity and protective-immunity studies in animals to examine the efficacy of this vaccine candidate as a measure to control PRRS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".