Identification of Genes Essential for Sulfamate and Fluorine Incorporation During Nucleocidin Biosynthesis
Bibliographic record
Abstract
Nucleocidin, a secondary metabolite of Streptomyces calvus (1), is a derivative of adenosine that contains 4’‐fluorine and 5’‐ O ‐sulfamate groups. Both substituents are rarely observed in natural products. A minimal biosynthetic gene cluster has yet to be defined for nucleocidin, and at least 24 genes appear to be involved. To date, only two functions have been assigned, neither of which are directly involved in sulfamate biosynthesis or fluorination (2, 3). In this presentation, we present biosynthetic studies on two newly discovered producers of nucleocidin, Streptomyces virens B‐24331 and Streptomyces aureorectus B‐24301 (4). Both strains are shown to be significantly (up to 30‐fold) better producers of nucleocidin than S. calvus . Gene disruption experiments in S. virens have identified, for the first time, genes differentially impacting sulfmate and 4’‐fluorine biosynthesis. These and additional results will be presented. References : (1) Zhu, X. M., et al., Biosynthesis of the Fluorinated Natural Product Nucleocidin in Streptomyces calvus Is Dependent on the bldA ‐Specified Leu‐tRNA(UUA) Molecule. ChemBioChem 2015 , 16 , 2498–2506. (2) Feng, X., et al . Two 3’‐ O ‐b‐glucosylated nucleoside fluorometabolites related to nucleocidin in Streptomyces calvus. Chem. Sci . 2019 , 10 , 9501‐9505. (3) Ngivprom, U., et al . Characterization of NucPNP and NucV involved in theearly steps of nucleocidin biosynthesis in Streptomyces calvus . RSC Adv., 2021 , 11 , 3510‐3515. (4) Chen, Y., et al., Streptomyces aureorectus DSM 41692 and Streptomyces virens DSM 41465 are producers of the antibiotic nucleocidin and 4’‐fluoroadenosine is identified as a co‐product. Org. Biomol. Chem . 2021 , DOI: 10.1039/d1ob01898a.
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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 | 0.000 | 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".