Molecular and cellular characterization of immunity conferred by lactobacilli against necrotic enteritis in chickens
Bibliographic record
Abstract
Necrotic enteritis is an important enteric disease of poultry that can be controlled with in-feed antibiotics. However, with the concerns over antimicrobial resistance, there is an increased interest in the use of alternatives. Probiotics are one of the alternatives that have gained considerable attention due to their antimicrobial and immunomodulatory activities. Therefore, in the present study, we evaluated the effects of two different Lactobacillus species alone or as a cocktail on prevention of necrotic enteritis. Day-old male broiler chickens were divided into five groups and on days 1, 8, 15, and 22, birds in groups 2 and 3 received 1×108 colony forming units (CFU) of L. johnsonii and L. reuteri, respectively. Group 4 received probiotic cocktails containing both bacteria (108 CFU/bird) and the negative and positive control groups did not receive any lactobacilli. Starting on day 23 post-hatch, birds in all groups (except the negative control group) were orally challenged twice per day with 3×108 CFU of a pathogenic C. perfringens strain for 3 days. Tissue and cecal samples were collected before and after challenge to assess gene expression, lymphocyte subsets determination, and microbiome analysis. On day 26 of age, lesion scoring was performed. The results demonstrated that the group that received the lactobacilli cocktail had significantly reduced lesion scores compared to the positive control group. In addition, the expression of interleukin (IL)-12 in the jejunum and CXC motif chemokine ligand 8 (CXCL8), IL-13, and IL-17 in the ileum were downregulated in the group that received the lactobacilli cocktail when compared to the positive control. Treating chickens with the lactobacilli cocktail prior to challenge enhanced the percentage of CD3-CD8+ cells and Bu-1+IgY+ B cells in the ileum and increased the frequency of monocyte/macrophages, CD3-CD8+ cells, Bu-1+IgM+, and Bu-1+IgY+ B cells in the jejunum. Treatment with the lactobacilli cocktail reduced the relative expression of Gamma-Protobacteria and Firmicutes compared to the positive control group. In conclusion, the results presented here suggest that treatment with the lactobacilli cocktail containing L. johnsonii and L. reuteri reduced necrotic enteritis lesions in the small intestine of chickens, possibly through the modulation of 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) | 0.000 | 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".