Functional effects of heating and cooling gene networks
Bibliographic record
Abstract
Abstract Everyday existence and survival of most organisms requires coping with temperature changes, which involves gene regulatory networks both as subjects and agents of cellular protection. Yet, how temperature affects gene network function remains unclear, partly because natural gene networks are complex and incompletely characterized. Here, we study how heating and cooling affect the function of single genes and well-characterized synthetic gene circuits in Saccharomyces cerevisiae . We found nontrivial, nonmonotone temperature-dependent gene expression trends at non-growth-optimal temperatures. In addition, heating caused unusual bimodality in the negative-feedback gene circuit expression and shifts upward the bimodal regime for the positive feedback gene circuit. Mathematical models incorporating temperature-dependent growth rates and Arrhenius scaling of reaction rates captured the effects of cooling, but not those of heating. Molecular dynamics simulations revealed that heating alters the conformational dynamics and allows DNA-binding of the TetR transcriptional repressor, fully explaining the experimental results for the negative-feedback gene circuit. Overall, we uncover how temperature shifts may corrupt gene networks, which may aid future designs of temperature-robust synthetic gene circuits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".