Cell wall biochemical alterations during <i>Agrobacterium</i>‐mediated expression of haemagglutinin‐based influenza virus‐like vaccine particles in tobacco
Bibliographic record
Abstract
Influenza virus-like particles (VLPs) have been shown to induce a safe and potent immune response through both humoral and cellular responses. They represent promising novel influenza vaccines. Plant-based biotechnology allows for the large-scale production of VLPs of biopharmaceutical interest using different model organisms, including Nicotiana benthamiana plants. Through this platform, influenza VLPs bud from the plasma membrane and accumulate between the membrane and the plant cell wall. To design and optimize efficient production processes, a better understanding of the plant cell wall composition of infiltrated tobacco leaves is a major interest for the plant biotechnology industry. In this study, we have investigated the alteration of the biochemical composition of the cell walls of N. benthamiana leaves subjected to abiotic and biotic stresses induced by the Agrobacterium-mediated transient transformation and the resulting high expression levels of influenza VLPs. Results show that abiotic stress due to vacuum infiltration without Agrobacterium did not induce any detectable modification of the leaf cell wall when compared to non infiltrated leaves. In contrast, various chemical changes of the leaf cell wall were observed post-Agrobacterium infiltration. Indeed, Agrobacterium infection induced deposition of callose and lignin, modified the pectin methylesterification and increased both arabinosylation of RG-I side chains and the expression of arabinogalactan proteins. Moreover, these modifications were slightly greater in plants expressing haemagglutinin-based VLP than in plants infiltrated with the Agrobacterium strain containing only the p19 suppressor of silencing.
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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".