Escherichia coli recombinant expression of SARS-CoV-2 protein fragments
Bibliographic record
Abstract
We have developed a method for the inexpensive, high-level expression of antigenic protein fragments of SARS-CoV-2 proteins in Escherichia coli. Our approach uses the thermophilic family 9 carbohydrate-binding module (CBM9) as an N-terminal carrier protein and affinity tag. The CBM9 module was joined to SARS-CoV-2 protein fragments via a flexible proline-threonine linker, which proved to be resistant to E. coli proteases. Two CBM9-spike protein fragment fusion proteins and one CBM9-nucleocapsid fragment fusion protein largely resisted protease degradation, while most of the CBM9 fusion proteins were degraded at some site in the SARS-CoV-2 protein fragment. All of the fusion proteins were highly expressed in E. coli and the CBM9-ID-H1 fusion protein was shown to yield 122 mg/L of purified product. Three purified CBM9-SARS-CoV-2 fusion proteins were tested and found to bind antibodies directed to the appropriate SARS-CoV-2 antigenic regions. The largest intact CBM9 fusion protein, CBM9-ID-H1, incorporates spike protein amino acids 540-588, which is a conserved region overlapping and C-terminal to the receptor binding domain that is widely recognized by human convalescent sera and contains a putative protective epitope.
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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 | 0.000 |
| 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".