Metabolomic Comparison and Assessment of Co-cultivation and a Heat-Killed Inducer Strategy in Activation of Cryptic Biosynthetic Pathways
Bibliographic record
Abstract
Co-cultivation has been used as a promising tool to turn on or up-regulate cryptic biosynthetic pathways for microbial natural product discovery. Recently, a modified culturing strategy similar to co-cultivation was investigated, where heat-killed inducer cultures were supplemented to the culture medium of producer fermentations to induce cryptic pathways. In the present study, the repeatability and effectiveness of both methods in turning on cryptic biosynthetic pathways were unbiasedly assessed using UHPLC-HRESIMS-based metabolomics analysis. Both induction methods had good repeatability, and they resulted in very different induced metabolites from the tested producers. Co-cultivation generated more induced mass features than the heat-killed inducer cultures, while both methods resulted in the induction of mass features not observed using the other induction method. As examples, pathways leading to two new natural products, N -carbamoyl-2-hydroxy-3-methoxybenzamide ( 1 ) and carbazoquinocin G ( 5 ), were induced and up-regulated through co-culturing a producer Streptomyces sp. RKND-216 with inducers Alteromonas sp. RKMC-009 and M. smegmatis ATCC 120515, respectively.
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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 | 0.001 |
| 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 | 0.000 |
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".