Expression of a Functional Single-Chain Variable-Fragment Antibody against Complement Receptor 1 in<i>Streptococcus gordonii</i>
Bibliographic record
Abstract
Streptococcus gordonii, an oral commensal organism, is a candidate vector for oral-vaccine development. Previous studies have shown that recombinant S. gordonii expressing heterologous antigens was weakly immunogenic when delivered intranasally. In this study, antigen was specifically targeted to antigen-presenting cells (APC) in order to potentiate antigen-APC interactions and increase the humoral immune response to the antigen. To achieve this goal, a single-chain variable-fragment (scFv) antibody against complement receptor 1 (CR1) was constructed. Anti-CR1 scFv purified from Escherichia coli was able to bind to mouse mixed lymphocytes and bone marrow-derived dendritic cells. The in vivo function of the anti-CR1 scFv protein was assessed by immunizing mice intranasally with soluble scFv and determining the immune response against the hemagglutinin (HA) peptide located on the carboxy terminus of the scFv. The serum anti-HA immunoglobulin G (IgG) immune response was dose dependent; as little as 100 ng of anti-CR1 scFv induced a significant IgG immune response, while such a response was minimal when the animals were given an unrelated scFv. The anti-CR1 scFv was expressed in S. gordonii as a secreted protein, which was functional, as it bound to dendritic cells. Mice orally colonized by the anti-CR1-secreting S. gordonii produced an anti-HA IgG immune response, indicating that such an approach can be used to increase the immune response to antigens produced by this bacterium.
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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) | 0.001 | 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".