Robust serum-free expansion of human B cells with an animal component-free cell culture supplement
Bibliographic record
Abstract
Abstract Human B cells are utilized in workflows for discovering therapeutic antibodies and in the developing field of cellular therapy. The ability to expand the B cell population in blood samples from pathogen-exposed or naive patients offers the opportunity to improve the recovery of antibody sequences, increase the diversity of the B cell repertoire, or achieve de novo immunization in vitro. It can be difficult, however, to obtain robust expansion of B cells in cultures. Addition of serum improves performance, albeit with high lot-to-lot variability, and introduces the risk of contamination by adventitious agents. We have developed an animal component-free (ACF) supplement for culturing human B cells that does not require the use of serum, feeder cells, or specialized culture plates to achieve robust in vitro expansion. The ACF supplement is a 50X concentrate comprising non-animal-derived recombinant proteins and factors that can be added to a suitable base medium of choice to promote B cell activation and expansion. Human pan-B cells isolated from peripheral blood mononuclear cells (leukopaks) by immunomagnetic enrichment could be cultured and expanded in standard 24-well tissue culture plates for over 30 days, starting with seeding densities of 1 × 105 cells/well and passaging every few days from day 7 (± 1 day) onwards. Though pronounced inter-donor cell variability was observed in the rate of proliferation, an average ~55-fold, ~110-fold and ~160-fold expansion of viable B cells was obtained after 7, 11 and 14 days of culture, respectively (n = 21 donors; range 27- to 1090-fold at day 14 ± 1 day). Differentiation to plasma cells was apparent by flow cytometric analysis of CD138 and CD20.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".