Characterization of vancomycin-resistance<i>vanD</i>gene clusters in the human intestinal microbiota by metagenomics and culture-enriched metagenomics
Bibliographic record
Abstract
Abstract Objectives To characterize vancomycin-resistance vanD gene clusters and potential vanD-carrying bacteria in the intestinal microbiota of healthy volunteers exposed or not to β-lactam antibiotics. Methods Stool samples were collected before and after 7 days of cefprozil β-lactam antibiotic exposure of 18 participants and six control participants who were not exposed to the antibiotic at the same time points. Metagenomic sequencing and culture-enriched metagenomic sequencing (with and without β-lactam selection) were used to characterize vanD gene clusters and determine potential vanD-carrying bacteria. Alteration by antimicrobials was also examined. Results Culture enrichment allowed detection of vanD genes in a large number of participants (11/24; 46%) compared to direct metagenomics (2/24; 8%). vanD genes were detected in stool cultures only following β-lactam exposure, either after β-lactam treatment of participants or after culture of stools with β-lactam selection. Six types of vanD gene clusters were identified. Two types of vanD cluster highly similar to those of enterococci were found in two participants. Other vanD genes or vanD clusters were nearly identical to those identified in commensal anaerobic bacteria of the families Lachnospiraceae and Oscillospiraceae and/or bordered by genomic sequences similar or related to these anaerobes, suggesting that they are the origin or carriers of vanD. Conclusions This study showed that culture-enriched metagenomics allowed detection of vanD genes not detected by direct metagenomics and revealed collateral enrichment of bacteria containing vancomycin-resistance vanD genes following exposure to β-lactams, with a higher prevalence of the most likely gut commensal anaerobes carrying vanD. These commensal anaerobes could be the reservoir of vanD genes carried by enterococci.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".