Purification of Plant-Derived Antibodies through Direct Immobilization of Affinity Ligands on Cellulose
Bibliographic record
Abstract
Plants possess enormous potential as factories for the large scale production of therapeutic reagents such as recombinant proteins and antibodies. A major factor limiting commercial advances of plant-derived pharmaceuticals is the cost and inefficiency of purification. As a model system, we have developed a simple yet robust method for immobilizing affinity capture ligands onto solid supports by interfacing the secreted expression and coupling of a chimeric fusion protein in Pichia pastoris to microcrystalline cellulose in a single step. The fusion protein, which consisted of antibody-binding proteins L and G fused to a cellulose-binding domain (LG-CBD), was tethered directly onto cellulose resins added to P. pastoris cultures and subsequently used for antibody purification. Both the antibody-binding protein L and protein G domains were functional, as demonstrated by the ability of cellulose-immobilized LG-CBD to purify both a scFv antibody fragment from yeast and a human IgG1 monoclonal antibody from transgenic tobacco. Furthermore, combining two P. pastoris strains expressing LG-CBD and scFv with CP-102 cellulose in a single culture allowed for easy recovery of biologically active scFv. Direct immobilization of affinity purification ligands, such as LG-CBD, onto inexpensive support matrices such as cellulose is an effective method for the generation of functional, single-use antibody purification reagents. Straightforward preparation of purification reagents will help make antibody purification from genetically modified crop plants feasible and address one of the major bottlenecks facing commercialization of plant-derived pharmaceuticals.
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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 | 0.001 |
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".