Rapid High-Yield Production of Functional SARS-CoV-2 Receptor Binding Domain by Viral and Non-Viral Transient Expression for Pre-Clinical Evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vaccine design strategies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are focused on the Spike protein or its subunits as the main antigen target of neutralizing antibodies. In this work, we propose rapid production methods of an extended segment of the Spike Receptor Binding Domain (RBD) in HEK293SF cells cultured in suspension, in serum-free media, as a major component of a COVID-19 subunit vaccine under development. The expression of RBD, engineered with a sortase-recognition motif for protein-based carrier coupling, was achieved at high yields by plasmid transient transfection or human type-5-adenoviral infection of the cells, in a period of only two and three weeks, respectively. Both production methods were evaluated in 3L-controlled bioreactors with upstream and downstream bioprocess improvements, resulting in a product recovery with over 95% purity. Adenoviral infection led to over 100 µg/mL of RBD in culture supernatants, which was around 7-fold higher than levels obtained in transfected cultures. The monosaccharide and sialic acid content was similar in the RBD protein from the two production approaches. It also exhibited a proper conformational structure as recognized by monoclonal antibodies directed against key native Spike epitopes. Efficient direct binding to ACE2 was also demonstrated at similar levels in RBD obtained from both methods and from different production lots. Overall, we provide bioprocess-related data for the rapid, scalable manufacturing of low cost RBD based vaccines against SARS-CoV-2, with the added value of making a functional antigen available to support further research on uncovering mechanisms of virus binding and entry as well as screening for potential COVID-19 therapeutics.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 it