Genome mining unveils widespread natural product biosynthetic capacity in human oral microbe Streptococcus mutans
Bibliographic record
Abstract
Streptococcus mutans is a major pathogen causing human dental caries. As a Gram-positive bacterium with a small genome (about 2 Mb) it is considered a poor source of natural products. Due to a recent explosion in genomic data available for S. mutans strains, we were motivated to explore the natural product production potential of this organism. Bioinformatic characterization of 169 publically available genomes of S. mutans from human dental caries revealed a surprisingly rich source of natural product biosynthetic gene clusters. Anti-SMASH analysis identified one nonribosomal peptide synthetase (NRPS) gene cluster, seven polyketide synthase (PKS) gene clusters and 136 hybrid PKS/NRPS gene clusters. In addition, 211 ribosomally synthesized and post-translationally modified peptides (RiPPs) clusters and 615 bacteriocin precursors were identified by a combined analysis using BAGEL and anti-SMASH. S. mutans harbors a rich and diverse natural product genetic capacity, which underscores the importance of probing the human microbiome and revisiting species that have traditionally been overlooked as "poor" sources of natural products.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".