Intracellular pH regulates ubiquitin-mediated degradation of the MAP kinase ERK3
Bibliographic record
Abstract
Intracellular pH (pHi) influences diverse cellular processes, including cell proliferation, metabolism, and migration, and is linked to metabolic diseases and cancer. Protonation alters protein charge and conformation, modulating different aspects of protein function. How pHi fluctuations are sensed by signaling proteins and translated into cellular responses remains incompletely understood. Here, we reveal that pHi plays a key role in regulating the stability of the mitogen-activated protein kinase Extracellular signal-regulated kinase 3 (ERK3). Intracellular acidification markedly increases the half-life of ERK3, whereas alkalinization accelerates its degradation. The pH-dependent regulation of ERK3 is rapid, reversible, and consistent across cell types. Mechanistically, we identified a region in the C-terminus of ERK3 that contains pH-sensing motifs. We further show by quantitative proteomics that short-term acidification or alkalinization globally affects the cellular proteome. Our findings underscore the critical role of pHi in ERK3 turnover and suggest a broader role for pH in regulating protein stability and cell signaling.
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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 | 0.000 | 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".