Evolution of iGluR ligand specificity, polyamine regulation, and ion selectivity inferred from a placozoan epsilon receptor
Bibliographic record
Abstract
Abstract Epsilon ionotropic glutamate receptors (iGluRs) are a recently defined clade of neurotransmitter receptors that are found in all major metazoan lineages that are distinct from α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), kainate, delta, phi (i.e., AKDF) and N -methyl-D-aspartate NMDA receptors. Here, we explore the evolution of iGluRs by generating a broad species-guided phylogeny of eukaryotic iGluRs and a comprehensive phylogeny of placozoan receptors, uncovering marked diversification of epsilon type receptors within Placozoa. Functional characterization of one epsilon receptor from the placozoan species Trichoplax adhaerens , named GluE1αA, reveals sensitivity to glycine, alanine, serine, and valine, but not glutamate. We demonstrate that changing just three amino acids in the ligand binding domain could convert ligand specificity of GluE1αA from glycine to glutamate, also causing nascent sensitivity to AMPA and increased sensitivity to the blocker 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX). We also demonstrate that an atypical serine in the pore Q/R/N site confers diminished Ca 2+ permeation and sensitivity to polyamine block, imposing similar effects on the human GluA2 receptor, and that a conserved aspartate four amino acids downstream of the Q/R/N site is crucial for polyamine regulation. Thus, key molecular determinants for polyamine regulation are conserved between AKDF and epsilon receptors.
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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 | 0.001 |
| 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".