Intestinal fungi are causally implicated in microbiome assembly and immune development in mice
Bibliographic record
Abstract
Abstract Gut microbiomes make major contributions to the physiological and immunological development of the host, but the relative importance of their bacterial and fungal components, and how they interact, remain largely unknown. We applied carefully controlled experiments in gnotobiotic mice colonized with defined communities of bacteria, fungi, or both to differentiate the direct role of fungi on microbiome assembly, host development, and susceptibility to colitis and airway inflammation. Our results revealed that fungal colonization alone was insufficient to promote the intestinal anatomic and physiological changes seen in mice colonized by bacteria, and had limited impact on the fecal metabolome. However, fungal colonization promoted major shifts in bacterial microbiome ecology, and had an independent effect on the innate and adaptive immune development in young mice. Fungi further exacerbated some aspects of the inflammatory effects of the bacterial community during OVA-induced airway inflammation by promoting macrophage infiltration in the airway. Our results demonstrate a dominant ecological and physiological role of bacteria in gut microbiomes, but highlight fungi as an ecological factor shaping the assembly of the bacterial community and a direct capacity to impact immune system and modulate disease susceptibility. These findings demonstrate that studies focused on bacteria alone provide an incomplete portrayal on microbiome ecology and functionality, and prompt for the inclusion of fungi in human microbiome studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".