bioRxivNeurosciencePreprint
Insular opioid signaling and distinct claustral ensembles in hedonic feeding
Jingyi CheniD, Leandra R. MangieriiD, Sophia Mar, Sean C. PiantadosiiD, David J. MarcusiD, Phoenix Davis, Benjamin Bruce LandiD, Michael R. BruchasiD
Abstract
Stress triggers eating that is driven by palatability rather than energy need, but how stress-related signals act on the circuits that control hedonic feeding is unclear. The claustrum, a thin sheet of neurons reciprocally connected with much of the cortex, is enriched in {kappa}-opioid receptors (KORs), the receptors for the stress-related peptide dynorphin. Here we show that a single forced swim increases palatable-food intake in mice without food restriction. Deleting or blocking claustral KOR attenuated this increase. A KOR-based sensor reported a fall in claustral opioid tone at the onset of eating. Prodynorphin (Pdyn)-expressing neurons in the anterior insular cortex (aIC) projected to the claustrum and recruited both vGAT and CaMKII-expressing claustral neurons. Single-cell imaging showed that eating engages claustral populations in distinct ways: nearly all vGAT neurons were activated, whereas KOR-Cre neurons divided into activated and suppressed subsets of similar size, with or without prior stress. vGAT responses to both sucrose and quinine grew after longer water restriction and scaled with licking, linking them to consummatory engagement rather than taste valence alone. Mice lacking Pdyn in the aIC ate more palatable food even without stress, and KOR ligands changed how mice engage with palatable food. These findings identify an insular-claustral opioid circuit through which stress can shape hedonic feeding.
- organism: mouse
- assay: scRNA-seq
- assay: behavioral assay
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: genetic perturbation / CRISPR
- approach: microscopy & imaging analysis
- approach: statistical model
- Citations
- 4
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