Cytosolic H<sup>+</sup> microdomain developed around AE1 during AE1‐mediated Cl<sup>−</sup>/HCO<sub>3</sub><sup>−</sup> exchange
Bibliographic record
Abstract
Microdomains, regions of discontinuous cytosolic solute concentration enhanced by rapid solute transport and slow diffusion rates, have many cellular roles. pH-regulatory membrane transporters, like the Cl−/HCO3− exchanger AE1, could develop H+ microdomains since AE1 has a rapid transport rate and cytosolic H+ diffusion is slow. We examined whether the pH environment surrounding AE1 differs from other cellular locations. As AE1 drives Cl−/HCO3− exchange, differences in pH, near and remote from AE1, were monitored by confocal microscopy using two pH-sensitive fluorescent proteins: deGFP4 (GFP) and mNectarine (mNect). Plasma membrane (PM) pH (defined as ∼1 μm region around the cell periphery) was monitored by GFP fused to AE1 (GFP.AE1), and mNect fused to an inactive mutant of the Na+-coupled nucleoside co-transporter, hCNT3 (mNect.hCNT3). GFP.AE1 to mNect.hCNT3 distance was varied by co-expression of different amounts of the two proteins in HEK293 cells. As the GFP.AE1–mNect.hCNT3 distance increased, mNect.hCNT3 detected the Cl−/HCO3− exchange-associated cytosolic pH change with a time delay and reduced rate of pH change compared to GFP.AE1. We found that a H+ microdomain 0.3 μm in diameter forms around GFP.AE1 during physiological HCO3− transport. Carbonic anhydrase isoform II inhibition prevented H+ microdomain formation. We also measured the rate of H+ movement from PM GFP.AE1 to endoplasmic reticulum (ER), using mNect fused to the cytosolic face of ER-resident calnexin (CNX.mNect). The rate of H+ diffusion through cytosol was 60-fold faster than along the cytosolic surface of the plasma membrane. The pH environment surrounding pH regulatory transport proteins may differ as a result of H+ microdomain formation, which will affect nearby pH-sensitive processes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".