Maternal rumen and milk microbiota shape the establishment of early-life rumen microbiota in grazing yak calves
Bibliographic record
Abstract
Early-life gut microbial colonization and development exert a profound impact on the health and metabolism of the host throughout the life span. The transmission of microbes from the mother to the offspring affects the succession and establishment of the early-life rumen microbiome in newborns, but the contributions of different maternal sites to the rumen microbial establishment remain unclear. In the present study, samples from different dam sites (namely, oral, rumen fluid, milk, and teat skin) and rumen fluid of yak calves were collected at 6 time points between d 7 and 180 postpartum to determine the contributions of the different maternal sites to the establishment of the bacterial and archaeal communities in the rumen during early life. Our analysis demonstrated that the dam's microbial communities clustered according to the sites, and the calves' rumen microbiota resembled that of the dam consistently regardless of fluctuations at d 7 and 14. The dam's rumen microbiota was the major source of the calves' rumen bacteria (7.9%) and archaea (49.7%) compared with the other sites, whereas the potential sources of the calf rumen microbiota from other sites varied according to the age. The contribution of dam's rumen bacteria increased with age from 0.36% at d 7 to 14.8% at d 180, whereas the contribution of the milk microbiota showed the opposite trend, with its contribution reduced from 2.7% at d 7 to 0.2% at d 180. Maternal oral archaea were the main sources of the calves' rumen archaea at d 14 (50.4%), but maternal rumen archaea became the main source gradually and reached 66.2% at d 180. These findings demonstrated the potential microbial transfer from the dam to the offspring that could influence the rumen microbiota colonization and establishment in yak calves raised under grazing regimens, providing the basis for future microbiota manipulation strategies during their early life.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 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".