Persistence of birth mode-dependent effects on gut microbiome composition, immune system stimulation and antimicrobial resistance during the first year of life
Bibliographic record
Abstract
Caesarean section delivery (CSD) disrupts mother-to-neonate transmission of specific microbial strains and functional repertoires as well as linked immune system priming. Here we investigate whether differences in microbiome composition and impacts on host physiology persist at 1 year of age. We perform high-resolution, quantitative metagenomic analyses of the gut microbiomes of infants born by vaginal delivery (VD) or by CSD, from immediately after birth through to 1 year of life. Several microbial populations show distinct enrichments in CSD-born infants at 1 year of age including strains of Bacteroides caccae, Bifidobacterium bifidum and Ruminococcus gnavus, whereas others are present at higher levels in the VD group including Faecalibacterium prausnitizii, Bifidobacterium breve and Bifidobacterium kashiwanohense. The stimulation of healthy donor-derived primary human immune cells with LPS isolated from neonatal stool samples results in higher levels of tumour necrosis factor alpha (TNF-α) in the case of CSD extracts over time, compared to extracts from VD infants for which no such changes were observed during the first year of life. Functional analyses of the VD metagenomes at 1 year of age demonstrate a significant increase in the biosynthesis of the natural antibiotics, carbapenem and phenazine. Concurrently, we find antimicrobial resistance (AMR) genes against several classes of antibiotics in both VD and CSD. The abundance of AMR genes against synthetic (including semi-synthetic) agents such as phenicol, pleuromutilin and diaminopyrimidine are increased in CSD children at day 5 after birth. In addition, we find that mobile genetic elements, including phages, encode AMR genes such as glycopeptide, diaminopyrimidine and multidrug resistance genes. Our results demonstrate persistent effects at 1 year of life resulting from birth mode-dependent differences in earliest gut microbiome colonisation.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".