Metaproteomic Profiling of Fungal Gut Colonization in Gnotobiotic Mice
Bibliographic record
Abstract
ABSTRACT Eukaryotic microbes can modulate mammalian host health and disease states, yet the molecular contribution of gut fungi remains nascent. We previously showed that mice exclusively colonized with fungi displayed increased sensitivity to allergic airway inflammation and fecal metabolite profiles similar to germ-free mice. To gain insights into the functional changes attributed to fungal colonization, we performed quantitative proteomic analyses of feces and small intestine of four-week-old gnotobiotic mice colonized with bacteria, fungi, or both. A comparison of fecal metaproteomic profiles between the mouse groups yielded broad changes in the relative levels of bacterial (46% of 2,860) and mouse (76% from 405) proteins. Many of the detected fungal proteins (3% of 1,492) have been previously reported as part of extracellular vesicles and having immunomodulating properties. Changes in the levels of mouse proteins derived from the jejunum (4% of 1,514) were mainly driven by proteins functional in lipid metabolism and apoptosis. Using metaproteomic profiling of gnotobiotic conditions, we show that fungal colonization profoundly impacts the host gut proteome. Our results suggest that an increased abundance of certain gut fungal species in early life may impact the developing intracellular balance of epithelial and immune cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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".