Gene editing of <i>Nicotiana benthamiana</i> architecture for space-efficient production of recombinant proteins in controlled environments
Bibliographic record
Abstract
Abstract Indoor vertical farming (VF) offers several practical advantages for the cultivation of plant protein bio-factories, including plant uniformity, product consistency, water/nutrient recycling and production cycles on a year-round basis. Much progress has been achieved in recent years toward the development of innovative systems for artificial lighting, automated irrigation, plant handling, environment control and space use optimization in VF systems. Here, we used a CRISPR-Cas9 gene editing approach to generate mutant lines of transient protein expression host Nicotiana benthamiana presenting a compact, space-efficient phenotype compared to the so-called LAB strain commonly used for protein production. Our strategy consisted of altering apical dominance by suppressing the biosynthesis of strigolactone, a negative regulator of axillary bud outgrowth-promoting cytokinins. Strigolactone-depleted lines were generated by knocking-down the expression of either Carotenoid cleavage dioxygenase 7 (CCD7) or Carotenoid cleavage dioxygenase 8 (CCD8), two key enzymes of the metabolic pathway leading to strigolactone synthesis. Knocking-down the genes of either enzyme had no impact on the overall growth rate of the plant but drastically influenced its leaf proteome, auxin/cytokinin ratio and overall architecture. More specifically, the ΔCCD mutants exhibited altered glycolytic and malate-processing enzyme fluxes driving the production of pyruvate and cytokinins in leaf tissue, an axillary growth-oriented development pattern and, most importantly, a spatial footprint reduced by 45% to 50% compared to the LAB strain. Most importantly, recombinant protein yields per plant were maintained in the mutant lines, as here illustrated for the model protein GFP and for rituximab, a chimeric monoclonal antibody of confirmed clinical value in humans. Our data demonstrate the usefulness of ΔCCD7 and ΔCCD8 knockout leading to strigolactone depletion for the generation of compact, space-efficient N. benthamiana lines well suited to VF systems intended for biopharmaceutical production.
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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) | 0.001 | 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".