Divergent maturational patterns of the infant bacterial and fungal gut microbiome in the first year of life are associated with inter-kingdom community dynamics and infant nutrition
Bibliographic record
Abstract
BACKGROUND: The gut microbiome undergoes primary ecological succession over the course of early life before achieving ecosystem stability around 3 years of age. These maturational patterns have been well-characterized for bacteria, but limited descriptions exist for other microbiota members, such as fungi. Further, our current understanding of the prevalence of different patterns of bacterial and fungal microbiome maturation and how inter-kingdom dynamics influence early-life microbiome establishment is limited. RESULTS: We examined individual shifts in bacterial and fungal alpha diversity from 3 to 12 months of age in 100 infants from the CHILD Cohort Study. We identified divergent patterns of gut bacterial or fungal microbiome maturation in over 40% of infants, which were characterized by differences in community composition, inter-kingdom dynamics, and microbe-derived metabolites in urine, suggestive of alterations in the timing of ecosystem transitions. Known microbiome-modifying factors, such as formula feeding and delivery by C-section, were associated with atypical bacterial, but not fungal, microbiome maturation patterns. Instead, fungal microbiome maturation was influenced by prenatal exposure to artificially sweetened beverages and the bacterial microbiome, emphasizing the importance of inter-kingdom dynamics in early-life colonization patterns. CONCLUSIONS: These findings highlight the ecological and environmental factors underlying atypical patterns of microbiome maturation in infants, and the need to incorporate multi-kingdom and individual-level perspectives in microbiome research to improve our understandings of gut microbiome maturation patterns in early life and how they relate to host health. Video Abstract.
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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".