290 Impact of altering maternal gut microbiome via high-forage or high-concentrate diets on offspring microbiome development, methane emissions and animal performance in cattle.
Bibliographic record
Abstract
Abstract Maternal gut microbiome has been shown to influence immune, metabolic and neurodevelopmental programming of offspring from the embryonic stage, suggesting a potential role in the Developmental Origins of Health and Disease (DOHaD). Whereas many still support the “sterile-womb hypothesis” that the neonatal microbiome acquisition occurs only during and after birth, very recent studies have provided evidence showing the existence of in utero microbial colonization. Thus, these recent developments in the field of microbiome research of human and vertebrate animals including bovine animals highlight that the maternal gut microbiome during pregnancy should be targeted for harnessing their extended impact on the offspring’s development and health. In this presentation, we will discuss the potential involvement of maternal microbiome and feto-maternal microbial crosstalk in fetal programming, and offspring calf’s health and development. In addition, we will discuss the results from our recently conducted longitudinal study focused on the evaluation of the impact of altering maternal microbiota via high forage or high concentrate diets on offspring microbiome development, energy balance, methane emissions and feedlot performance in beef cattle. For this, 120 beef heifers were assigned to one of two treatments and received a diet based on 75% forage (HF) or 75% concentrate (HC) from 15 days pre-breeding through calving. Heifers were bred using male-sexed semen and fed to target a gain of 0.45kg/d for both groups. Ruminal fluid, fecal and vaginal swabs were collected from both HF (n = 24) and HC (n =22) heifers on pre-breeding (-30, -2), post-breeding (56, 91, 180, and 238 days of gestation) and at calving. Calves born from these heifers were monitored for their animal performance, feed efficiency, gut microbiome development and enteric methane emission (in vitro and in vivo). Body weight measurements, ruminal fluid and fecal samples were collected from the calves at 0, 15, 30, 60, 120, 160, 240, 330 and 340 days old. The 16S rNRA gene sequencing was performed on the dam and calf’s microbiome samples. An in-vitro fermentation assay was performed on the ruminal fluid samples from heifers and their calves for methane and VFA analyses. During finishing stage, a subset of calves born from HF and HC dams (n = 10 each group) were evaluated to examine effects on energy metabolism, nutrient balance and enteric methane emission (using headbox) output between the HF and HC offspring because of the HF or HC diet their dams received during fetal development. The results from this study provide novel insights into the impact of altered maternal gut microbiome during pregnancy on the postnatal animal performance, feed efficiency, microbiome development and enteric methane emission phenotype in cattle.
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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 | 0.000 | 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) | 0.001 | 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".