Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation
Bibliographic record
Abstract
BACKGROUND: Members of the Bacteroidales, particularly Bacteroides species, with their ability to degrade dietary fibers and liberate otherwise unavailable substrates, exert a substantial influence on the microbiome of the lower intestine. However, our understanding of how this influence translates to the metabolic interactions that support community structure remains limited. In this study, we apply constraint-based modeling to investigate metabolic interactions in chicken cecal communities categorized by the presence or absence of Bacteroides. RESULTS: From metagenomic datasets previously generated from 33 chicken ceca, we constructed 237 metagenome-assembled genomes. Metabolic modeling of communities built from these genomes generated profiles of short-chain fatty acids largely consistent with experimental assays and confirmed the role of B. fragilis as a metabolic hub, central to the production of metabolites consumed by other taxa. In its absence, communities undergo significant functional reconfiguration, with metabolic roles typically fulfilled by B. fragilis assumed by multiple taxa. Beyond B. fragilis, we found Escherichia coli and Lactobacillus crispatus also mediate influential metabolic roles, which vary in the presence or absence of B. fragilis. Notably, the microbiome's compensatory adaptations in the absence of B. fragilis produced metabolic alterations resembling those previously associated with inflammatory bowel disease in humans, including energy deficiency, increased lactate production, and altered amino acid metabolism. CONCLUSIONS: This work demonstrates the potential of using the chicken cecal microbiome as a model system for investigating the complex metabolic interactions and key contributions that drive community dynamics in the gut. Our model-based predictions offer insights into how keystone taxa like B. fragilis may shape the metabolic landscape and functional organization of microbial communities. The observed metabolic adaptations in the absence of B. fragilis share metabolic similarities with profiles seen in dysbiotic states in humans and underscore the translational relevance of these insights for understanding gut health across different host systems. Video Abstract.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".