Breathing air to save energy – new insights into the ecophysiological role of high‐affinity [NiFe]‐hydrogenase in <i>Streptomyces avermitilis</i>
Bibliographic record
Abstract
The Streptomyces avermitilis genome encodes a putative high-affinity [NiFe]-hydrogenase conferring the ability to oxidize tropospheric H2 in mature spores. Here, we used a combination of transcriptomic and mutagenesis approaches to shed light on the potential ecophysiological role of the enzyme. First, S. avermitilis was either exposed to low or hydrogenase-saturating levels of H2 to investigate the impact of H2 on spore transcriptome. In total, 1293 genes were differentially expressed, with 1127 and 166 showing lower and higher expression under elevated H2 concentration, respectively. High H2 exposure lowered the expression of the Sec protein secretion pathway and ATP-binding cassette-transporters, with increased expression of genes encoding proteins directing carbon metabolism toward sugar anabolism and lower expression of NADH dehydrogenase in the respiratory chain. Overall, the expression of relA responsible for the synthesis of the pleiotropic alarmone ppGpp decreased upon elevated H2 exposure, which likely explained the reduced expression of antibiotic synthesis and stress response genes. Finally, deletion of hhySL genes resulted in a loss of H2 uptake activity and a dramatic loss of viability in spores. We propose that H2 is restricted to support the seed bank of Streptomyces under a unique survival-mixotrophic energy mode and discuss important ecological implications of this finding.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".