Receptor-independent membrane mediated pathways of serotonin action
Bibliographic record
Abstract
Abstract Serotonin is a neurotransmitter as well as a somatic signaling molecule, and the serotonergic system is a major target for psychotropic drugs. Serotonin, together with a few related neurotransmitters, has recently been found to exhibit an unexpectedly high lipid membrane affinity 1–3 . It has been conjectured that extrasynaptic serotonin can diffuse in the lipid membrane to efficiently reach remote receptors (and receptors with buried ligand-binding sites) 4 , providing a mechanism for the diffuse ‘volume’ neurotransmission that serotonin is capable of 5–10 . Here we show that membrane binding by serotonin can directly modulate membrane properties and cellular function, independent of its receptor-mediated actions. Atomic force microscopy shows that serotonin binding makes artificial lipid bilayers softer. It induces nucleation of liquid disordered domains inside the raft-like liquid-ordered domains in a ternary bilayer displaying phase separation. Solid-state NMR spectroscopy corroborates this data, revealing a rather homogeneous decrease in the order parameter of the lipid chains in the presence of serotonin. In the RN46A immortalized serotonergic neuronal cell line, extracellular serotonin enhances transferrin receptor endocytosis, an action exerted even in the presence of both broad-spectrum serotonin receptor and transporter inhibitors. Similarly, it increases the binding and internalization of Islet Amyloid Polypeptide (IAPP) oligomers, suggesting a connection between serotonin, which is co-secreted with IAPP by pancreatic beta cells, and the cellular effects of IAPP. Our results uncover a hitherto unknown serotonin-bilayer interaction that can potentiate key cellular processes in a receptor-independent fashion. Therefore, some pathways of serotonergic action may escape potent pharmaceutical agents designed for serotonin transporters or receptors. Conversely, bio-orthogonal serotonin-mimetics may provide a new class of cell-membrane modulators.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".