Systems biosynthesis of secondary metabolic pathways within the oral human microbiome member <i>Streptococcus mutans</i>
Bibliographic record
Abstract
Streptococcus mutans, a Gram-positive human commensal and pathogen, is commonly recognized as a primary causative agent in dental caries. Metabolic activity of this strain results in the creation of acids and secreted products are recognized as pathogenic factors and agents that promote immunomodulation by stimulating the release of pro-inflammatory cytokines. Products of secondary metabolic pathways of microorganisms from the human microbiome are increasingly investigated for their immunomodulatory functions. In this study, we sought to explore the metabolomic output of nonribosomal peptide pathways within the model S. mutans strain, S. mutans UA159, using a systems metabolomic approach to gain in-depth analysis on products created by this organism and probe these molecules for their immunomodulatory function. Comparative metabolomics and biosynthetic studies using wild-type and nonribosomal peptide deletion strains (within the mutanobactin biosynthetic locus), precursor feedings (fatty acid derivatives) led to the identification of 58 metabolites, 13 of which were structurally elucidated. In addition to these, an assembly line derailment product, mutanamide, was also identified and used to assess immunomodulatory properties of mutanobactins and actions relating to their previously reported functions describing hyphal inhibitory profiles in Candida albicans. The results of this study demonstrate both the complexity and the divergent roles of products stemming from this unique biosynthetic assembly line.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".