Fundamental limits to progression of cellular life in frigid environments
Bibliographic record
Abstract
ABSTRACT Life on Earth, including for microbes and cold-blooded animals, often occurs in frigid environments. At frigid temperatures, nearly all intracellular processes slow down which is colloquially said to decelerate life’s pace and, potentially, aging. But even for one cell, an outstanding conceptual challenge is rigorously explaining how the slowed-down intracellular processes collectively sustain a cell’s life and set its pace. Here, by monitoring individual yeast cells for months at near-freezing temperatures, we show how global gene-expression dynamics and Reactive Oxygen Species (ROS) act together as the primary factors that dictate and constrain the pace at which a budding yeast’s life can progresses in frigid environments. We discovered that yeast cells help each other in surviving and dividing at frigid temperatures. By investigating the underlying mechanism, involving glutathione secretion, we discovered that ROS is the primary determinant of yeast’s ability to survive and divide at near-freezing temperatures. Observing days-to-months-long cell-cycle progression in individual cells revealed that ROS inhibits S-G2-M (replicative) phase while elongating G1 (growth) phase up to a temperature-dependent threshold duration, beyond which yeast cannot divide and bursts as an unsustainably large cell. We discovered that an interplay between global gene-expression speed and ROS sets the threshold G1-duration by measuring rates of genome-wide transcription and protein synthesis at frigid temperatures and then incorporating them into a mathematical model. The same interplay yields unbeatable “speed limits” for cell cycling – shortest and longest allowed doubling times – at each temperature. These results establish quantitative principles for engineering cold-tolerant microbes and reveal how frigid temperatures can fundamentally constrain microbial life and cell cycle at the systems-level.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".