A human gut bacterial genome and culture collection for improved metagenomic analyses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding gut microbiome functions requires cultivated bacteria for experimental validation and reference bacterial genome sequences to interpret metagenome datasets and guide functional analyses. We present the Human Gastrointestinal Bacteria Culture Collection (HBC), a comprehensive set of 737 whole-genome-sequenced bacterial isolates, representing 273 species (105 novel species) from 31 families found in the human gastrointestinal microbiota. The HBC increases the number of bacterial genomes derived from human gastrointestinal microbiota by 37%. The resulting global Human Gastrointestinal Bacteria Genome Collection (HGG) classifies 83% of genera by abundance across 13,490 shotgun-sequenced metagenomic samples, improves taxonomic classification by 61% compared to the Human Microbiome Project (HMP) genome collection and achieves subspecies-level classification for almost 50% of sequences. The improved resource of gastrointestinal bacterial reference sequences circumvents dependence on de novo assembly of metagenomes and enables accurate and cost-effective shotgun metagenomic analyses of human gastrointestinal microbiota.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it