Microbiota Transplantation in Day-Old Broiler Chickens Ameliorates Necrotic Enteritis via Modulation of the Intestinal Microbiota and Host Immune Responses
Bibliographic record
Abstract
A microbiota transplant (MT) originating from mature adult chicken ceca and propagated in bioreactors was administered to day-old broiler chicks to ascertain the degree to which, and how, the MT affects Clostridium perfringens (Cp)-incited necrotic enteritis (NE). Using a stress predisposition model of NE, birds administered the MT and challenged with Cp showed fewer necrotic lesions, and exhibited a substantially higher α- and β-diversity of bacteria in their jejunum and ceca. Birds challenged with Cp and not administered the MT showed decreased Lactobacillus and increased Clostridium sensu strico 1 in the jejunum. In ceca, Megamonas, a genus containing butyrate-producing bacteria, was only present in birds administered the MT, and densities of this genus were increased in birds challenged with Cp. Metabolite profiles in cecal digesta were altered in birds administered the MT and challenged with the pathogen; 59 metabolites were differentially abundant following MT treatment, and the relative levels of short chain fatty acids, butyrate, valerate, and propionate, were decreased in birds with NE. Birds administered the MT and challenged with Cp showed evidence of enhanced restoration of intestinal barrier functions, including elevated mRNA of MUC2B, MUC13, and TJP1. Likewise, birds administered the MT exhibited higher mRNA of IL2, IL17A, and IL22 at 2-days post-inoculation with Cp, indicating that these birds were better immunologically equipped to respond to pathogen challenge. Collectively, study findings demonstrated that administering a MT containing a diverse mixture of microorganisms to day-old birds ameliorated NE in broilers by increasing bacterial diversity and promoting positive immune responses.
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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) | 0.000 | 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 | 0.001 |
| 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".