An industrial-grade Nicotiana benthamiana line for the production of glycoproteins carrying fucose-free galactosylated N-glycans
Bibliographic record
Abstract
β1,4-galactosylation is a typical human N-glycan formation with functional impact on proteins, particularly known for IgGs. Therefore, the expression of recombinant proteins with controlled galactosylation is an important quality parameter in the biotech industry. Here we describe the establishment of a plant-based expression platform for the manufacturing of recombinant proteins carrying β1,4-galactosylated N-glycans. A genome-edited Nicotiana benthamiana glycosylation mutant (NbXF-KO) that synthesizes conserved eukaryotic GnGn structures served as a template for further elongation toward β1,4-galactosylated N-glycans. A hybrid β1,4-galactosyltransferase gene that targets the enzyme to a post-Golgi compartment was introduced into the NbXF-KO genome without any additional foreign DNA sequence. The efficient generation of “marker-free” transgenic lines (NbXF-KO Gal ) was achieved by using a dual-vector strategy and visual screening procedures. Of note, a monoclonal antibody expressed in NbXF-KO Gal exhibited up to 70 % galactosylated, fucose/xylose-free N-glycans, in a batch-to-batch consistent manner. Given recent findings attributing anti-inflammatory activities to nonfucosylated, galactosylated IgG, our results gain new significance. • Multi-gene-edited knockout Nicotiana benthamiana is suited for stable expansion of plant N-glycosylation. • The platform expresses recombinant proteins carrying fucose-free β1,4-galactosylated N-glycans. • Glycan engineered plants are free of any marker sequences. • A dual-vector strategy allowed efficient generation and screening of marker-free transgenic plants. • Compared to mass spectrometry, a simplified approach was developed to assess the abundance of β1,4-galactosylated N-glycans.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".