Discovery of 3′-<i>O</i>-β-Glucosyltubercidin and the Nucleoside Specific Glycosyltransferase AvpGT through Genome Mining
Bibliographic record
Abstract
A genome mining approach was used to identify a hybrid tubercidin–nucleocidin biosynthetic gene cluster (BGC) in Streptomyces sp. AVP053U2. Analysis of culture extracts by liquid chromatography–mass spectrometry revealed the presence of a glucosylated tubercidin derivative. A gene, avpGT, was identified within the hybrid cluster that has homology to the glucosyltransferase that is responsible for 3′- O -β-glucosylation of the fluorinated natural product nucleocidin. AvpGT was heterologously expressed and purified from Escherichia coli for in vitro characterization. AvpGT is active toward UDP-glucose and UDP-galactose as glycosyl donors and several nucleosides as acceptors. Kinetic analysis revealed that AvpGT is most specific for UDP-glucose [ k cat / K M app = (1.1 ± 0.3) × 10 5 M –1 ·s –1 ] as the glycosyl donor and tubercidin [ k cat / K M app = (5.3 ± 1.8) × 10 4 M –1 ·s –1 ] as the glycosyl acceptor. NMR spectroscopic analysis revealed the product of this reaction to be 3′- O -β-glucopyranosyl tubercidin. A sequence analysis of AvpGT reveals a family of nucleoside-specific GTs, which may be used as markers of BGCs that produce glycosylated nucleosides.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".