A molecular mechanism for high salt taste in <i>Drosophila</i>
Bibliographic record
Abstract
SUMMARY Dietary salt detection and consumption are crucial to maintaining fluid and ionic homeostasis. To optimize salt intake, animals employ salt-dependent activation of multiple taste pathways. Generally, sodium activates attractive taste cells, but attraction is overridden at high salt concentrations by cation non-selective activation of aversive taste cells. In flies, high salt avoidance is driven by both ‘bitter’ taste neurons and a class of glutamatergic ‘high salt’ neurons expressing pickpocket23 (ppk23). Although the cellular basis of salt taste has been described, many of the molecular mechanisms remain elusive. Here, we show that ionotropic receptor 7c (IR7c) is expressed in glutamatergic high salt neurons, where it functions with co-receptors IR76b and IR25a to detect high salt. Misexpression of IR7c in sweet neurons, which endogenously express IR76b and IR25a, confers responsiveness to non-sodium salts, indicating that IR7c is sufficient to convert a sodium-selective receptor to a cation non-selective receptor. Furthermore, the resultant transformation of taste neuron tuning switches potassium chloride from an aversive to an attractive tastant. This research provides insight into the molecular basis of monovalent and divalent salt taste coding and the full repertoire of IRs needed to form a functional salt receptor.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".