Taxonomic and functional assessment using metatranscriptomics reveals the effect of Angus cattle on rumen microbial signatures
Bibliographic record
Abstract
A greater understanding of the rumen microbiota and its function may help find new strategies to improve feed efficiency in cattle. This study aimed to investigate whether the cattle breed affects specific ruminal taxonomic microbial groups and functions associated with feed conversion ratio (FCR), using two genetically related Angus breeds as a model. Total RNA was extracted from 24 rumen content samples collected from purebred Black and Red Angus bulls fed the same forage diet and then subjected to metatranscriptomic analysis. Multivariate discriminant analysis (sparse partial least square discriminant analysis (sPLS-DA)) and analysis of composition of microbiomes were conducted to identify microbial signatures characterizing Black and Red Angus cattle. Our analyses revealed relationships among bacterial signatures, host breeds and FCR. Although Black and Red Angus are genetically similar, sPLS-DA detected 25 bacterial species and 10 functions that differentiated the rumen microbial signatures between those two breeds. In Black Angus, we identified bacterial taxa Chitinophaga pinensis, Clostridium stercorarium and microbial functions with large and small subunits ribosomal proteins L16 and S7 exhibiting a higher abundance in the rumen microbiome. In Red Angus, nonetheless, we identified the poorly characterized bacterial taxon Oscillibacter valericigenes with a higher abundance and pathways related to carbohydrate metabolism. Analysis of composition of microbiomes revealed that C. pinensis and C. stercorarium exhibited a higher abundance in Black Angus compared to Red Angus associated with FCR, suggesting that these bacterial species may play a key role in the feed conversion efficiency of forage-fed bulls. This study highlights how the discovery of signatures of bacterial taxa and their functions can be used to harness the full potential of the rumen microbiome in Angus cattle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".