Application of culturomics to characterize diverse anaerobic bacteria from the gastrointestinal tract of broiler chickens in relation to environmental reservoirs
Bibliographic record
Abstract
Characterization of the microbiota of chickens is of current interest. The goals of the current study were to apply anaerobic isolation methods to comprehensively isolate and identify bacteria from the gastrointestinal tract of chickens and their environment. Bacterial communities within the drinking water were dominated by Escherichia, whereas communities in litter were more representative of the cecum. The crop and small intestine (jejunum and ileum) were dominated by Lactobacillus and Enterococcus spp., and the cecum was dominated by Proteus spp. The collection of bacteria isolated was dominated by Enterococcus spp., Escherichia/Shigella spp., Lactobacillus spp., and Proteus spp.; however, many rare taxa were observed. These included members of the Clostridiales and Clostridium spp., which were commonly isolated from the ileum and cecum. Bacteria isolated by enrichment and direct plating differed. The selective de Man–Rogosa–Sharpe agar was commonly associated with the isolation of Lactobacillus spp. and yielded the lowest diversity of all methods utilized. Increased diversity and frequency of Clostridium spp. was observed in enrichments of blood and mucus or by plating on Columbia agar supplemented with 10% blood and gentamicin. The bacteria isolated from this study provide source material for genomic and functional studies in chicken hosts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".