Different antibiotic growth promoters induce specific changes in the cecal microbiota membership of broiler chicken
Bibliographic record
Abstract
Antimicrobials are sometimes given to food animals at low doses in order to promote faster growth. However, the mechanisms by which those drugs improve performance are not fully understood. This study aimed to investigate the impact of zinc bacitracin (55g/ton), enramycin (10g/ton); halquinol® (30g/ton); virginiamycin (16,5g/ton) and avilamycin (10g/ton) on the cecal microbiota of broiler chicken, compared to a control group. Six hundred and twenty four chicks (Cobb 500) arriving to an experimental unit were randomly assigned into each treatment with four repetitions per treatment. The cecal content of 16 animals per treatment (n = 96) was used for DNA extraction and sequencing of the V4 region of the 16S rRNA gene using Illumina technology. The use of antimicrobials induced significant changes in membership but not in structure of the cecal microbiota compared to the control group, suggesting a greater impact on the less abundant species of bacteria present in that environment. Halquinol was the only drug that did not affect microbial membership. Firmicutes comprised the major bacterial phylum present in the cecum of all groups. There was no statistical difference in relative abundances of the main phyla between treated animals and the control group (all P>0.05). Treatment with enramycin was associated with decreased richness and with lower relative abundance of unclassified Firmicutes, Clostridium XI, unclassified Peptostreptococcaceae (all P<0.001) and greater abundance of Clostridium XIVb (P = 0.004) and Anaerosporobacter spp. (P = 0.015), and treatment with bacitracin with greater relative abundance of Bilophila spp. (P = 0.004). Several bacterial genera were identified as representative of usage of each drug. This study used high throughput sequencing to characterize the impact of several antimicrobials in broiler chicken under controlled conditions and add new insights to the current knowledge on how AGPs affect the cecal microbiota of chicken.
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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".