Expression of a constitutively active nitrate reductase increases SARS‐CoV‐2 Spike protein production in <i>Nicotiana benthamiana</i> leaves that otherwise show traits of senescence
Bibliographic record
Abstract
The production of coronavirus disease 2019 vaccines can be achieved by transient expression of the Spike (S) protein of Severe Acute Respiratory Syndrome Coronavirus 2 in agroinfiltrated leaves of Nicotiana benthamiana, a process promoted by the co-expression of viral silencing suppressor P19. Upon expression, the S protein enters the cell secretory pathway, before being trafficked to the plasma membrane where formation of coronavirus-like particles (CoVLPs) occurs. We recently used RNAseq and time course sampling to characterize molecular responses of N. benthamiana leaf cells expressing P19 only or P19 in combination with recombinant S protein. This revealed expression of the viral proteins to deeply affect the physiological status of plant cells, including through the activation of immune responses. Here, transcriptomics shows that the production of CoVLPs also induces leaf senescence, as revealed by the up-regulation of senescence-associated genes, activation of senescence-related proteases and down-regulation of genes involved in basic metabolic functions like photosynthesis or nitrogen uptake and assimilation. CoVLP production also up-regulates asparagine synthetase genes and leads to the consequent accumulation of asparagine, a nitrogen-rich amino acid known to facilitate reallocation of nitrogen resources from senescent to young growing organs. Hypothesizing these combined host responses to restrain foreign protein accumulation, an attempt was made to support nitrogen reduction in CoVLP-producing leaves by co-expressing a constitutively active, light-insensitive form of nitrate reductase. We show this strategy to increase S protein accumulation in leaf tissues, thereby suggesting that boosting nitrogen metabolism in agroinfiltrated leaves may improve recombinant protein yields in N. benthamiana.
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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".