Multiomics analysis reveals the presence of a microbiome in the gut of fetal lambs
Bibliographic record
Abstract
OBJECTIVE: Microbial exposure is critical to neonatal and infant development, growth and immunity. However, whether a microbiome is present in the fetal gut prior to birth remains debated. In this study, lambs delivered by aseptic hysterectomy at full term were used as an animal model to investigate the presence of a microbiome in the prenatal gut using a multiomics approach. DESIGN: Lambs were euthanised immediately after aseptic caesarean section and their cecal content and umbilical cord blood samples were aseptically acquired. Cecal content samples were assessed using metagenomic and metatranscriptomic sequencing to characterise any existing microbiome. Both sample types were analysed using metabolomics in order to detect microbial metabolites. RESULTS: was the most abundant species in the prenatal fetal gut. We also detected multiple microbial metabolites including short chain fatty acids, deoxynojirimycin, mitomycin and tobramycin, further indicating the presence of metabolically active microbiota. Additionally, bacteriophage phiX174 and Orf virus, as well as antibiotic resistance genes, were detected in the fetal gut, suggesting that bacteriophage, viruses and bacteria carrying antibiotic resistance genes can be transmitted from the mother to the fetus during the gestation period. CONCLUSIONS: This study provides strong evidence that the prenatal gut harbours a microbiome and that microbial colonisation of the fetal gut commences in utero.
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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".