Regulation of iron–sulphur cluster homeostasis through transcriptional control of the <scp>Isc</scp> pathway by [2<scp>Fe</scp>–2<scp>S</scp>]–<scp>IscR</scp> in <i><scp>E</scp>scherichia coli</i>
Bibliographic record
Abstract
Fe-S clusters are essential across the biological world, yet how cells regulate expression of Fe-S cluster biogenesis pathways to cope with changes in Fe-S cluster demand is not well understood. Here, we describe the mechanism by which IscR, a [2Fe-2S] cluster-containing regulator of Escherichia coli, adjusts the synthesis of the Isc Fe-S biogenesis pathway to maintain Fe-S homeostasis. Our data indicate that a negative feedback loop operates to repress transcription of the iscRSUA-hscBA-fdx operon, encoding IscR and the Isc machinery, through binding of [2Fe-2S]-IscR to two upstream binding sites. IscR was shown to require primarily the Isc pathway for synthesis of its Fe-S cluster, providing a link between IscR activity and demands for Fe-S clusters through the levels of the Isc system. Surprisingly, the isc operon was more repressed under anaerobic conditions, indicating increased Fe-S cluster occupancy of IscR and decreased Fe-S cluster biogenesis demand relative to aerobic conditions. Consistent with this notion, overexpression of a Fe-S protein under aerobic conditions, but not under anaerobic conditions, led to derepression of P(iscR). Together, these data show how transcriptional control of iscRSUA-hscBA-fdx by [2Fe-2S]-IscR allows E. coli to respond efficiently to varying Fe-S demands.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".