Metagenomic analysis provides bases on individualized shift of colon microbiome affected by delaying colostrum feeding in neonatal calves
Bibliographic record
Abstract
This study investigated the effect of colostrum feeding time on the colon digesta microbiome of 2-day-old dairy calves using whole-genome-based metagenome sequencing, aiming to understand the dynamic changes of the colon microbiome when the colostrum feeding is delayed. In total, 24 male Holstein calves were grouped to different pasteurized colostrum feeding time treatments randomly: TRT0h (45 min after birth,n = 7); TRT6h (6 h after birth,n = 8); and TRT12h (12 h after birth,n = 9). Bacteria, archaea, eukaryotes, and viruses were identified in the colon microbiome, with bacteria (99.20%) being the most predominant domain.Streptococcus,Clostridium,Lactobacillus,Ruminococcus, andEnterococcuswere the top five abundant bacteria genera. For colon microbiome functions, 114 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified, with nutrients metabolism-related functions “carbohydrate metabolism,” “amino acid metabolism,” “metabolism of cofactors and vitamins,” “metabolism of terpenoids and polyketides,” and “metabolism of other amino acids” being the top five secondary level of KEGG hierarchy functions. When colon microbiomes were compared, they were not affected by delaying first colostrum feeding at both taxonomic and functional levels. However, distinct clusters of colon microbiome profiles were shown based on PERMANOVA analysis despite of different colostrum feeding treatment, suggesting the individualized responses. Moreover, the relative abundance of microbial taxa, microbial functions, and differentially expressed genes was compared between the two distinct clusters, and different relationships were observed among host differentially expressed genes, differential levels of microbial taxa, and microbial functions between the two clusters. Our results suggest that the host may play an important role in shaping the colon microbiome of neonatal dairy calves in response to the early life feeding management. Whether the observed colon microbiome shifts affect gut health and function in the long term requires further research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".