Communal living: glycan utilization by the human gut microbiota
Bibliographic record
Abstract
Our lower gastrointestinal tract plays host to a vast consortium of microbes, known as the human gut microbiota (HGM). The HGM thrives on a complex and diverse range of glycan structures from both dietary and host sources, the breakdown of which requires the concerted action of cohorts of carbohydrate-active enzymes (CAZymes), carbohydrate-binding proteins, and transporters. The glycan utilization profile of individual taxa, whether 'specialist' or 'generalist', is dictated by the number and functional diversity of these glycan utilization systems. Furthermore, taxa in the HGM may either compete or cooperate in glycan deconstruction, thereby creating a complex ecological web spanning diverse nutrient niches. As a result, our diet plays a central role in shaping the composition of the HGM. This review presents an overview of our current understanding of glycan utilization by the HGM on three levels: (i) molecular mechanisms of individual glycan deconstruction and uptake by key bacteria, (ii) glycan-mediated microbial interactions, and (iii) community-scale effects of dietary changes. Despite significant recent advancements, there remains much to be discovered regarding complex glycan metabolism in the HGM and its potential to affect positive health outcomes.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".