Research Note: Clostridium perfringens NetB and CnaA neutralizing nanobodies in feed reduce the incidence of poultry necrotic enteritis
Bibliographic record
Abstract
Necrotic enteritis is a devastating disease to poultry caused by the bacterium Clostridium perfringens. As a novel approach to combating poultry necrotic enteritis, we identified and characterized several hundred single domain antibody fragments (or nanobodies) capable of binding either the NetB toxin or the collagen-binding adhesin (CnaA) of C. perfringens. Many of the nanobodies could neutralize the in vitro functions of NetB or CnaA with inhibitory concentrations in the nanomolar range. The nanobodies were also screened for proteolytic stability in an extract derived from gastrointestinal tract fluids of chickens. A collection of 6 nanobodies (4 targeting NetB and 2 targeting CnaA) with high neutralizing activity and high gastrointestinal tract extract stability were expressed and secreted by Pichia pastoris or Bacillus subtilis. Chickens were given a feed with 1 of the 2 nanobody-containing groups: 1) nanobody-containing P. pastoris supernatants that were semi-purified, lyophilized, and enterically coated, or 2) B. subtilis spores from strains containing the nanobody genes. Compared to untreated chickens (23.75% mortality), mortality of chickens receiving feed modified with the P. pastoris and B. subtilis products decreased to 11.25 and 7.5%, respectively. These results offer a new opportunity to improve the control of poultry necrotic enteritis by incorporating highly specific nanobodies or bacteria expressing these nanobodies directly into chicken feed.
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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) | 0.002 | 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".