<i>Streptomyces</i> volatile compounds influence exploration and microbial community dynamics by altering iron availability
Bibliographic record
Abstract
ABSTRACT Bacteria and fungi produce a wide array of volatile organic compounds (VOCs), and these can act as infochemicals or as competitive tools. Recent work has shown that the VOC trimethylamine (TMA) can promote a new form of Streptomyces growth, termed ‘exploration’. Here, we report that TMA also serves to alter nutrient availability in the area surrounding exploring cultures: TMA dramatically increases the environmental pH, and in doing so, reduces iron availability. This, in turn, compromised the growth of other soil bacteria and fungi. In contrast, Streptomyces thrives in these iron-depleted niches by secreting a suite of differentially modified siderophores, and by upregulating genes associated with siderophore uptake. Further reducing iron levels by siderophore piracy, limiting siderophore uptake, or growing cultures in the presence of iron chelators, unexpectedly enhanced exploration. Our work reveals a new role for VOCs in modulating iron levels in the environment, and implies a critical role for VOCs in modulating the behaviour of microbes and the makeup of their communities.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".