Detection and Identification of <i>Lactobacillus</i> Species in Crops of Broilers of Different Ages by Using PCR-Denaturing Gradient Gel Electrophoresis and Amplified Ribosomal DNA Restriction Analysis
Bibliographic record
Abstract
The microflora of the crop was investigated throughout the broiler production period (0 to 42 days) using PCR combined with denaturing gradient gel electrophoresis (PCR-DGGE) and selective bacteriological culture of lactobacilli followed by amplified ribosomal DNA restriction analysis (ARDRA). The birds were raised under conditions similar to those used in commercial broiler production. Lactobacilli predominated and attained populations of 10(8) to 10(9) CFU per gram of crop contents. Many of the lactobacilli present in the crop (61.9% of isolates) belonged to species of the Lactobacillus acidophilus group and could not be differentiated by PCR-DGGE. A rapid and simple ARDRA method was developed to distinguish between the members of the L. acidophilus group. HaeIII-ARDRA was used for preliminary identification of isolates in the L. acidophilus group and to identify Lactobacillus reuteri and Lactobacillus salivarius. MseI-ARDRA generated unique patterns for all species of the L. acidophilus group, identifying Lactobacillus crispatus, Lactobacillus johnsonii, and Lactobacillus gallinarum among crop isolates. The results of our study provide comprehensive knowledge of the Lactobacillus microflora in the crops of birds of different ages using nucleic acid-based methods of detection and identification based on current taxonomic criteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".