Mutation of a conserved glutamine residue does not abolish desensitization of acid-sensing ion channel 1
Bibliographic record
Abstract
Desensitization is a common feature of ligand-gated ion channels, although the molecular cause varies widely between channel types. Mutations that greatly reduce or nearly abolish desensitization have been described for many ligand-gated ion channels, including glutamate, GABA, glycine, and nicotinic receptors, but not for acid-sensing ion channels (ASICs) until recently. Mutating Gln276 to a glycine (Q276G) in human ASIC1a was reported to mostly abolish desensitization at both the macroscopic and the single channel levels, potentially providing a valuable tool for subsequent studies. However, we find that in both human and chicken ASIC1, the effect of Q276G is modest. In chicken ASIC1, the equivalent Q277G slightly reduces desensitization when using pH 6.5 as a stimulus but desensitizes, essentially like wild-type, when using more acidic pH values. In addition, steady-state desensitization is intact, albeit right-shifted, and recovery from desensitization is accelerated. Molecular dynamics simulations indicate that the Gln277 side chain participates in a hydrogen bond network that might stabilize the desensitized conformation. Consistent with this, destabilizing this network with the Q277N or Q277L mutations largely mimics the Q277G phenotype. In human ASIC1a, the Q276G mutation also reduces desensitization, but not to the extent reported previously. Interestingly, the kinetic consequences of Q276G depend on the human variant used. In the common G212 variant, Q276G slows desensitization, while in the rare D212 variant desensitization accelerates. Our data reveal that while the Q/G mutation does not abolish or substantially impair desensitization as previously reported, it does point to unexpected differences between chicken and human ASICs and the need for careful scrutiny before using this mutation in future studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".