Characterization and analysis of an industrial strain of<i>Streptomyces bingchenggensis</i>by genome sequencing and gene microarray
Bibliographic record
Abstract
Streptomyces bingchenggensis is a soil bacterium that produces milbemycins, a family of macrolide antibiotics that are commercially important in crop protection and veterinary medicine. In addition, S. bingchenggensis produces many other natural products including the polyether nanchangmycin and novel cyclic pentapeptides. To identify the gene clusters involved in the biosynthesis of these compounds, and better clarify the biochemical pathways of these gene clusters, the whole genome of S. bingchenggensis was sequenced, and the transcriptome profile was subsequently investigated by microarray. In comparison with other sequenced genomes in Streptomyces, S. bingchenggensis has the largest linear chromosome consisting of 11 936 683 base pairs (bp), with an average GC content of 70.8%. The 10 023 predicted protein-coding sequences include at least 47 gene clusters correlated with the biosynthesis of known or predicted secondary metabolites. Transcriptional analysis demonstrated an extremely high expression level of the milbemycin gene cluster during the entire growth period and a moderately high expression level of the nanchangmycin gene cluster during the initial hours that subsequently decreased. However, other gene clusters appear to be silent. The genome-wide analysis of the secondary metabolite gene clusters in S. bingchenggensis, coupled with transcriptional analysis, will facilitate the rational development of high milbemycins-producing strains as well as the discovery of new 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 0.001 |
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".