A High-Yield <em>Streptomyces</em> Transcription-Translation Toolkit for Synthetic Biology and Natural Product Applications
Bibliographic record
Abstract
Streptomyces spp. are a major source of clinical antibiotics and industrial chemicals. Streptomyces venezuelae ATCC 10712 is a fast-growing strain and a natural producer of chloramphenicol, jadomycin, and pikromycin, which makes it an attractive candidate as a next-generation synthetic biology chassis. Therefore, genetic tools that accelerate the development of S. venezuelae ATCC 10712, as well as other Streptomyces spp. models, are highly desirable for natural product engineering and discovery. To this end, a dedicated S. venezuelae ATCC 10712 cell-free system is provided in this protocol to enable high-yield heterologous expression of high G+C (%) genes. This protocol is suitable for small-scale (10-100 μL) batch reactions in either 96-well or 384-well plate format, while reactions are potentially scalable. The cell-free system is robust and can achieve high yields (~5-10 μM) for a range of recombinant proteins in a minimal setup. This work also incorporates a broad plasmid toolset for real-time measurement of mRNA and protein synthesis, as well as in-gel fluorescence staining of tagged proteins. This protocol can also be integrated with high-throughput gene expression characterization workflows or the study of enzyme pathways from high G+C (%) genes present in Actinomycetes genomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.017 |
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".