Molecular Diversity of Methanogens in Feedlot Cattle from Ontario and Prince Edward Island, Canada
Bibliographic record
Abstract
The molecular diversity of rumen methanogens in feedlot cattle and the composition of the methanogen populations in these animals from two geographic locations were investigated using 16S rRNA gene libraries prepared from pooled PCR products from 10 animals in Ontario (127 clones) and 10 animals from Prince Edward Island (114 clones). A total of 241 clones were examined, with Methanobrevibacter ruminantium accounting for more than one-third (85 clones) of the clones identified. From these 241 clones, 23 different 16S rRNA phylotypes were identified. Feedlot cattle from Ontario, which were fed a corn-based diet, revealed 11 phylotypes (38 clones) not found in feedlot cattle from Prince Edward Island, whereas the Prince Edward Island cattle, which were fed potato by-products as a finishing diet, had 7 phylotypes (42 clones) not found in cattle from Ontario. Five sequences, representing the remaining 161 clones (67% of the clones), were common in both herds. Of the 23 different sequences, 10 sequences (136 clones) were 89.8 to 100% similar to those from cultivated methanogens belonging to the orders Methanobacteriales, Methanomicrobiales, and Methanosarcinales, and the remaining 13 sequences (105 clones) were 74.1 to 75.8% similar to those from Thermoplasma volcanium and Thermoplasma acidophilum. Overall, nine possible new species were identified from the two clone libraries, including two new species belonging to the order Methanobacteriales and a new genus/species within the order Methanosarcinales. From the present survey, it is difficult to conclude whether the geographical isolation between these two herds or differences between the two finishing diets directly influenced community structure in the rumen. Further studies are warranted to properly assess the differences between these two finishing diets.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".