A Novel Approach to Development of Monoclonal Antibodies Using Native Antigen for Immunization and Recombinant Antigen for Screening
Bibliographic record
Abstract
The production of monoclonal antibodies (MAb) specific to microbes is rapidly growing. Finding an appropriate antigen to screen hybridoma clones has become increasingly important. However, the conventional method, in which the purified antigen from the microbe is routinely used for screening, cannot avoid selection of false positive hybridoma clones, since even highly purified antigen is found to be contaminated with some other proteins from the microbe. In this study, MAbs against anthrax protective antigen (PA), the central component of the three-part toxin secreted by Bacillus anthracis were developed using a pair of the roughly purified native PA as an immunogen and the recombinant PA as a screening antigen without any possibility of false selection, since the recombinant PA was produced by a gene engineering approach and impossible to be contaminated with any other proteins from B. anthracis. In total, nine stable hybridoma clones secreting anti-PA MAbs were developed. All of them had the same type of heavy and light chains, IgG1/kappa. The binding profiles for these anti-PA MAbs were investigated by ELISA. This novel approach to the development of MAbs should be applicable to the production of MAbs to other microbes, especially to those from which antigens can hardly be purified to a high degree.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".