Environmental and Gut Bacteroidetes: The Food Connection
Bibliographic record
Abstract
Members of the diverse bacterial phylum Bacteroidetes have colonized virtually all types of habitats on Earth. They are among the major members of the microbiota of animals, especially in the gastrointestinal tract, can act as pathogens and are frequently found in soils, oceans and freshwater. In these contrasting ecological niches, Bacteroidetes are increasingly regarded as specialists for the degradation of high molecular weight organic matter, i.e., proteins and carbohydrates. This review presents the current knowledge on the role and mechanisms of polysaccharide degradation by Bacteroidetes in their respective habitats. The recent sequencing of Bacteroidetes genomes confirms the presence of numerous carbohydrate-active enzymes covering a large spectrum of substrates from plant, algal, and animal origin. Comparative genomics reveal specific Polysaccharide Utilization Loci shared between distantly related members of the phylum, either in environmental or gut-associated species. Moreover, Bacteroidetes genomes appear to be highly plastic and frequently reorganized through genetic rearrangements, gene duplications and lateral gene transfers (LGT), a feature that could have driven their adaptation to distinct ecological niches. Evidence is accumulating that the nature of the diet shapes the composition of the intestinal microbiota. We address the potential links between gut and environmental bacteria through food consumption. LGT can provide gut bacteria with original sets of utensils to degrade otherwise refractory substrates found in the diet. A more complete understanding of the genetic gateways between food-associated environmental species and intestinal microbial communities sheds new light on the origin and evolution of Bacteroidetes as animals' symbionts. It also raises the question as to how the consumption of increasingly hygienic and processed food deprives our microbiota from useful environmental genes and possibly affects our health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".