Genome-wide analysis of intracellular pH reveals quantitative control of cell division rate by pHc in Saccharomyces cerevisiae
Bibliographic record
Abstract
BACKGROUND: Because protonation affects the properties of almost all molecules in cells, cytosolic pH (pH(c)) is usually assumed to be constant. In the model organism yeast, however, pH(c) changes in response to the presence of nutrients and varies during growth. Since small changes in pH(c) can lead to major changes in metabolism, signal transduction, and phenotype, we decided to analyze pH(c) control. RESULTS: Introducing a pH-sensitive reporter protein into the yeast deletion collection allowed quantitative genome-wide analysis of pH(c) in live, growing yeast cultures. pH(c) is robust towards gene deletion; no single gene mutation led to a pH(c) of more than 0.3 units lower than that of wild type. Correct pH(c) control required not only vacuolar proton pumps, but also strongly relied on mitochondrial function. Additionally, we identified a striking relationship between pH(c) and growth rate. Careful dissection of cause and consequence revealed that pH(c) quantitatively controls growth rate. Detailed analysis of the genetic basis of this control revealed that the adequate signaling of pH(c) depended on inositol polyphosphates, a set of relatively unknown signaling molecules with exquisitely pH sensitive properties. CONCLUSIONS: While pH(c) is a very dynamic parameter in the normal life of yeast, genetically it is a tightly controlled cellular parameter. The coupling of pH(c) to growth rate is even more robust to genetic alteration. Changes in pH(c) control cell division rate in yeast, possibly as a signal. Such a signaling role of pH(c) is probable, and may be central in development and tumorigenesis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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".