Impact of Feed Efficiency and Diet on Adaptive Variations in the Bacterial Community in the Rumen Fluid of Cattle
Bibliographic record
Abstract
Limited knowledge of the structure and activities of the ruminal bacterial community prevents the understanding of the effect of population dynamics on functional bacterial groups and on host productivity. This study aimed to identify particular bacteria associated with host feed efficiency in steers with differing diets and residual feed intake (RFI) using culture-independent methods: PCR-denaturing gradient gel electrophoresis (DGGE) and quantitative real-time PCR analysis. PCR-DGGE profiles were generated from the ruminal fluid of 55 steers fed a low-energy-density diet and then switched to a high-energy-density diet. Bacterial profile comparisons by multivariate statistical analysis showed a trend only for RFI-related clusters on the high-energy diet. When steers (n = 19) belonging to the same RFI group under both diets were used to identify specific bacterial phylotypes related to feed efficiency traits, correlations were detected between dry matter intake, average daily gain, and copy numbers of the 16S rRNA gene of Succinivibrio sp. in low-RFI (efficient) steers, whereas correlations between Robinsoniella sp. and RFI (P < 0.05) were observed for high-RFI (inefficient) animals. Eubacterium sp. differed significantly (P < 0.05) between RFI groups that were only on the high-energy diet. Our work provides a comprehensive framework to understand how particular bacterial phylotypes contribute to differences in feed efficiency and ultimately influence host productivity, which may either depend on or be independent from diet factors.
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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".