A Two-Step Mechanism for the Activation of Actinorhodin Export and Resistance in Streptomyces coelicolor
Bibliographic record
Abstract
Many microorganisms produce secondary metabolites that have antibiotic activity. To avoid self-inhibition, the producing cells often encode cognate export and/or resistance mechanisms in the biosynthetic gene clusters for these molecules. Actinorhodin is a blue-pigmented antibiotic produced by Streptomyces coelicolor. The actAB operon, carried in the actinorhodin biosynthetic gene cluster, encodes two putative export pumps and is regulated by the transcriptional repressor protein ActR. In this work, we show that normal actinorhodin yields require actAB expression. Consistent with previous in vitro work, we show that both actinorhodin and its 3-ring biosynthetic intermediates [e.g., (S)-DNPA] can relieve repression of actAB by ActR in vivo. Importantly, an ActR mutant that interacts productively with (S)-DNPA but not with actinorhodin responds to the actinorhodin biosynthetic pathway with the induction of actAB and normal yields of actinorhodin. This suggests that the intermediates are sufficient to trigger the export genes in actinorhodin-producing cells. We further show that actinorhodin-producing cells can induce actAB expression in nonproducing cells; however, in this case actinorhodin is the most important signal. Finally, while the "intermediate-only" ActR mutant permits sufficient actAB expression for normal actinorhodin yields, this expression is short-lived. Sustained culture-wide expression requires a subsequent actinorhodin-mediated signaling step, and the defect in this response causes widespread cell death. These results are consistent with a two-step model for actinorhodin export and resistance where intermediates trigger initial expression for export from producing cells and actinorhodin then triggers sustained export gene expression that confers culture-wide resistance. IMPORTANCE Understanding the links between antibiotic resistance and biosynthesis is important for our efforts to manipulate secondary metabolism. For example, many secondary metabolites are produced at low levels; our work suggests that manipulating export might be one way to enhance yields of these molecules. It also suggests that understanding resistance will be relevant to the generation of novel secondary metabolites through the creation of synthetic secondary metabolic gene clusters. Finally, these cognate resistance mechanisms are related to mechanisms that arise in pathogenic bacteria, and understanding them is relevant to our ability to control microbial infections clinically.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".