Functional Production and Characterization of a Fibrin-Specific Single-Chain Antibody Fragment from<i>Bacillus subtilis</i>: Effects of Molecular Chaperones and a Wall-Bound Protease on Antibody Fragment Production
Bibliographic record
Abstract
To develop an ideal blood clot imaging and targeting agent, a single-chain antibody (SCA) fragment based on a fibrin-specific monoclonal antibody, MH-1, was constructed and produced via secretion from Bacillus subtilis. Through a systematic study involving a series of B. subtilis strains, insufficient intracellular and extracytoplasmic molecular chaperones and high sensitivity to wall-bound protease (WprA) were believed to be the major factors that lead to poor production of MH-1 SCA. Intracellular and extracytoplasmic molecular chaperones apparently act in a sequential manner. The combination of enhanced coproduction of both molecular chaperones and wprA inactivation leads to the development of an engineered B. subtilis strain, WB800HM[pEPP]. This strain allows secretory production of MH-1 SCA at a level of 10 to 15 mg/liter. In contrast, with WB700N (a seven-extracellular-protease-deficient strain) as the host, no MH-1 SCA could be detected in both secreted and cellular fractions. Secreted MH-1 SCA from WB800HM[pMH1, pEPP] could be affinity purified using a protein L matrix. It retains comparable affinity and specificity as the parental MH-1 monoclonal antibody. This expression system can potentially be applied to produce other single-chain antibody fragments, especially those with folding and protease sensitivity problems.
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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 | 0.000 |
| 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 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".