Scalable agroinfiltration-based production of SARS-CoV-2 antigens for use in diagnostic assays and subunit vaccines
Bibliographic record
Abstract
Agroinfiltration is a method used in biopharming to support plant-based biosynthesis of therapeutic proteins such as antibodies and viral antigens involved in vaccines. Major advantages of generating proteins in plants is the low cost, massive scalability and the rapid yield of the technology. Herein, we report the agroinfiltration-based production of glycosylated SARS-CoV-2 Spike receptor-binding domain (RBD) protein. We show that it exhibits high-affinity binding to the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) and displays folding similar to antigen produced in mammalian expression systems. Moreover, our plant-expressed RBD was readily detected by IgM, IgA, and IgG antibodies from the serum of SARS-CoV-2 infected and vaccinated individuals. We further demonstrate that binding of plant-expressed RBD to ACE2 is efficiently neutralized by these antibodies. Collectively, these findings demonstrate that recombinant RBD produced via agroinfiltration exhibits suitable biochemical and antigenic features for use in serological and neutralization assays, and in subunit vaccine platforms.
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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 | 0.001 |
| 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".