Transient Expression of Dengue Virus NS1 Antigen in Nicotiana benthamiana for Use as a Diagnostic Antigen
Bibliographic record
Abstract
Dengue is a viral disease that represents a significant threat to global public health since billions of people are now at risk of infection by this mosquito-borne virus. The implementation of extensive screening tests is indispensable to control this disease, and the Dengue virus non-structural protein 1 (NS1) is a promising antigen for the serological diagnosis of dengue fever. Plant-based systems can be a safe and cost-effective alternative for the production of dengue virus antigens. In this work, two strategies to produce the dengue NS1 protein in Nicotiana benthamiana leaves were evaluated: Targeting NS1 to five different subcellular compartments to assess the best subcellular organelle for the expression and accumulation of NS1, and the addition of elastin-like polypeptide (ELP) or hydrophobin (HFBI) fusion tags to NS1. The transiently expressed proteins in N. benthamiana were quantified by Western blot analysis. The NS1 fused to ELP and targeted to the ER (NS1 ELP-ER) showed the highest yield (445 mg/kg), approximately a forty-fold increase in accumulation levels compared to the non-fused protein (NS1-ER), representing the first example of transient expression of DENV NS1 in plant. We also demonstrated that NS1 ELP-ER was successfully recognized by a monoclonal anti-dengue virus NS1 glycoprotein antibody, and by sera from dengue virus-infected patients. Interestingly, it was found that transient production of NS1-ER and NS1 ELP-ER using vacuum infiltration of whole plants, which is easier to scale up, rather than syringe infiltration of leaves, greatly improved the accumulation of NS1 proteins. The generated plant made NS1, even without extensive purification, showed potential to be used for the development of the NS1 diagnostic tests in resource-limited areas where dengue is endemic.
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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 | 0.000 |
| 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) | 0.000 | 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".