Molecular responses of agroinfiltrated <i>Nicotiana benthamiana</i> leaves expressing suppressor of silencing P19 and influenza virus-like particles
Bibliographic record
Abstract
Summary The production of influenza vaccines in plants is achieved through transient Agrobacterium -mediated expression of viral hemagglutinins (HAs). These proteins are produced and matured through the secretory pathway of plant cells, before being trafficked to the plasma membrane where they induce formation of virus-like particles (VLPs). Production of VLPs unavoidably impacts plant cells, as do viral suppressors of RNA silencing (VSRs) that are often co-expressed to increase protein yields. However, little information is available on host molecular responses to these foreign proteins. The present work provides a comprehensive overview of transcriptomic, metabolic, and signaling changes occurring in Nicotiana benthamiana leaf cells transiently expressing the VSR P19, or co-expressing P19 and an influenza HA. Our data identifies generic responses to Agrobacterium -mediated expression of foreign proteins, including shutdown of chloroplast gene expression, activation of oxidative stress responses, and reinforcement of the plant cell wall through lignification. Our results also indicate that P19 expression promotes salicylic acid (SA) signaling, a process apparently antagonized by co-expression of HA. As the latter induces specific signatures, with effects on lipid metabolism, lipid distribution, and oxylipin signaling, dampening of P19 responses suggests crosstalk between SA and oxylipin pathways. Consistent with the upregulation of oxidative stress-related genes and proteins, we finally show that reduction of oxidative stress damage through exogenous application of ascorbic acid improves plant biomass quality during production of VLPs. One-sentence summary Agrobacterium -mediated expression of influenza virus-like particles induces a unique molecular signature in Nicotiana benthamiana leaf cells.
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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".