Functional Recovery of AQP2 Recessive Mutations Through Hetero-Oligomerization with Wild-Type Counterpart
Bibliographic record
Abstract
Aquaporin-2 (AQP2) is a homotetrameric water channel responsible for the final water reuptake in the kidney. Mutations in the protein induce nephrogenic diabetes insipidus (NDI), which challenges the water balance by producing large urinary volumes. Although recessive AQP2 mutations are believed to generate non-functional and monomeric proteins, the literature identifies several mild mutations which suggest the existence of mixed wt/mut tetramers likely to carry function in heterozygotes. Using Xenopus oocytes, we tested this hypothesis and found that mild mutants (V24A, D150E) can associate with wt-AQP2 in mixed heteromers, providing clear functional gain in the process (62 ± 17% and 63 ± 17% increases, respectively), conversely to the strong monomeric R187C mutant which fails to associate with wt-AQP2. In kidney cells, both V24A and D150E display restored targeting while R187C remains in intracellular stores. Using a collection of mutations to expand recovery analyses, we demonstrate that inter-unit contacts are central to this recovery process. These results not only present the ground data for the functional recovery of recessive AQP2 mutants through heteromerization, which prompt to revisit the accepted NDI model, but more importantly describe a general recovery process that could impact on all multimeric systems where recessive mutations are found.
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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".