Unraveling the interaction between the phageome and bacteriome in the rumen and its role in influencing metabolome dynamics in dairy cows at different lactation stages
Bibliographic record
Abstract
BACKGROUND: Although the roles of rumen microbiome in milk yield and milk protein synthesis have been widely recognized, knowledge on how ruminal microbiome dynamic changes affect these two traits during the whole lactation is lacking. Phages have been shown to affect the microbiota, but little is known about the shift patterns of ruminal phages and if they may modulate rumen microbiome during lactation. Herein, a longitudinal study was performed to identify the potential roles of ruminal phageome and bacteriome interactions, and metabolic function shift in affecting milk yield and protein content using metagenomic and metabolomic profiling of rumen microbiome from the peak, early, and later mid-lactation stages. RESULTS: A total of 780 ruminal bacterial phages were identified, which exhibited two primary shifting patterns: (1) decreasing then increasing; (2) decreasing then stabilizing through the lactation. Bacteriome also showed first increasing then stabilizing or continuously declining besides exhibiting two similar shifting patterns to those of phages. By associating the differentially abundant phages with their host bacteria, we observed that significantly increased Lactococcus phage BM13, Corynebacterium phage P1201, and Campylobacter phage CJIE4-5 in peak lactation, along with Lactobacillus phage Lv-1 in early and later mid-lactation, were positively correlated with the relative abundance of their hosts. However, significantly increased Bacillus phage BCU4 and the Enterococcus phage phiNASRA1 in early mid-lactation were negatively related to their host abundance. In terms of bacteria, Ruminococcus flavefaciens and Faecalibacterium sp. CAG 74 had the highest abundance in peak lactation, whereas most Prevotella species were more abundant in early and later mid-lactation. Notably, ruminal carbohydrate and amino acid metabolism functions were enhanced in early mid-lactation. Further structural equation model and network analysis revealed that abundant Bacillus phage BCU4 and Enterococcus phage phiNASRA1 in early mid-lactation were associated with increased relative abundance of Prevotella species, possibly due to a reduction in Bacillus cereus and Enterococcus faecalis. Additionally, these Prevotella species exhibited positive relationships with rumen metabolites, such as L-phenylalanine, phenylacetylglycine, N-acetyl-D-phenylalanine, and propionate content, which contributed to the improved milk protein yield. CONCLUSIONS: This study revealed the bacteriome and phageome interactions at different lactation stages, and the key phages and bacteria regulating the rumen function and metabolism thus contributing to the milk traits of cows. The potential regulatory roles of phages in affecting the rumen bacteriome suggest that they can be powerful targets for future interventions to improve rumen functions. Video Abstract.
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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".