A ubiquitous <i>Streptomyces</i> biosynthetic megacluster encodes an arsenal of synergistic biotin-targeting antibiotics
Bibliographic record
Abstract
Abstract The rise of multidrug-resistant pathogens underscores the urgent need for antibiotics that act through new targets and mechanisms. Biotin metabolism, essential in most bacteria, remains underexploited therapeutically. Here, we uncover a highly conserved, co-located biosynthetic megacluster in Streptomyces , a striking “cluster of clusters”, that encodes four distinct natural product families: acidomycin, stravidins, dapamycins, and α-methyl-KAPA, and is flanked by genes that encode streptavidin, a high-affinity biotin-binding protein. Remarkably, all molecules target different steps in bacterial biotin metabolism, revealing a multi-pronged natural strategy for biotin starvation. This arrangement of four functionally convergent biosynthetic gene clusters at a single genomic locus is without precedent. Even more surprisingly, we find that this anti-biotin megacluster is widespread across Streptomyces bacteria, suggesting a deeply conserved evolutionary solution to microbial competition. Mechanistically, the compounds inhibit biotin biosynthesis through enzyme blockade, prodrug activation, covalent cofactor mimicry, and biotin sequestration via co-expressed streptavidin. Stravidin S2 and α-methyl-KAPA are effective in a murine model of multidrug-resistant E. coli infection. These findings expose a coordinated biosynthetic logic in microbial secondary metabolites and point to higher-order biosynthetic architectures as promising reservoirs of antibiotic innovation.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".