Cryptic specialized metabolites drive <i>Streptomyces</i> exploration and provide a competitive advantage during growth with other microbes
Bibliographic record
Abstract
Streptomyces bacteria have a complex life cycle that is intricately linked with their remarkable metabolic capabilities. Exploration is a recently discovered developmental innovation of these bacteria, that involves the rapid expansion of a structured colony on solid surfaces. Nutrient availability impacts exploration dynamics, and we have found that glycerol can dramatically increase exploration rates and alter the metabolic output of exploring colonies. We show here that glycerol-mediated growth acceleration is accompanied by distinct transcriptional signatures and by the activation of otherwise cryptic metabolites including the orange-pigmented coproporphyrin, the antibiotic chloramphenicol, and the uncommon, alternative siderophore foroxymithine. Exploring cultures are also known to produce the well-characterized desferrioxamine siderophore. Mutational studies of single and double siderophore mutants revealed functional redundancy when strains were cultured on their own; however, loss of the alternative foroxymithine siderophore imposed a more profound fitness penalty than loss of desferrioxamine during coculture with the yeast Saccharomyces cerevisiae . Notably, the two siderophores displayed distinct localization patterns, with desferrioxamine being confined within the colony area, and foroxymithine diffusing well beyond the colony boundary. The relative fitness advantage conferred by the alternative foroxymithine siderophore was abolished when the siderophore piracy capabilities of S. cerevisiae were eliminated ( S. cerevisiae encodes a ferrioxamine-specific transporter). Our work suggests that exploring Streptomyces colonies can engage in nutrient-targeted metabolic arms races, deploying alternative siderophores that allow them to successfully outcompete other microbes for the limited bioavailable iron during coculture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".