Expressions of resistome is linked to the key functions and stability of active rumen microbiome
Bibliographic record
Abstract
BACKGROUND: The resistome describes the array of antibiotic resistant genes (ARGs) present within a microbial community. Recent research has documented the resistome in the rumen of ruminants and revealed that the type and abundance of ARGs could be affected by diet and/or antibiotic treatment. However, most of these studies only assessed ARGs using metagenomics, and expression of the resistome and its biological function within the microbiome remains largely unexplored. RESULTS: We characterized the pools of ARGs (resistome) and their activities in the rumen of 48 beef cattle belonging to three breeds (Angus, Charolais, Kinsella composite hybrid), using shotgun metagenomics and metatranscriptomics. Sixty (including 20 plasmid-associated) ARGs were expressed which accounted for about 30% of the total number of ARGs (187) identified in metagenomic datasets, with tetW and mefA exhibiting the highest level of expression. In addition, the bacterial hosts of 17 expressed ARGs were identified. The active resistome was less diverse in Kinsella composite hybrid than Angus, however, expression of ARGs did not differ among breeds. Although not associated with feed efficiency, the total abundance of expressed ARGs was positively correlated with metabolic pathways and 'attenuation values' (a measurement of stability) of the active rumen microbiome, suggesting that ARGs expression influences the stability and functionality of the rumen microbiome. Moreover, Ruminococcus spp., Prevotella ruminicola, Muribaculaceae spp. and Collinsella aerofaciens were all identified as hosts of expressed ARGs, possibly promoting the dominance of these carbohydrate degraders within the rumen microbiome. CONCLUSIONS: Findings from this study provide new insight into the active rumen resistome in vivo, which may inform strategies to limit the spread of ubiquitously found ARGs from the rumen to the broader environment without negatively impacting the key functional outcomes of the rumen microbiome.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".