Acute inhibition of hunger-sensing AgRP neurons promotes context-specific learning in mice.

AgRP neurons Chemogenetics Conditioning Hunger Optogenetics Photometry

Journal

Molecular metabolism
ISSN: 2212-8778
Titre abrégé: Mol Metab
Pays: Germany
ID NLM: 101605730

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 28 02 2023
revised: 29 08 2023
accepted: 06 09 2023
pubmed: 11 9 2023
medline: 11 9 2023
entrez: 10 9 2023
Statut: ppublish

Résumé

An environmental context, which reliably predicts food availability, can increase the appetitive food drive within the same environment context. However, hunger is required for the development of such a context-induced feeding (CIF) response, suggesting the neural circuits sensitive to hunger link an internal energy state with a particular environment context. Since Agouti related peptide (AgRP) neurons are activated by energy deficit, we hypothesised that AgRP neurons are both necessary and sufficient to drive CIF. To examine the role of AgRP neurons in the CIF process, we used fibre photometry with GCaMP7f, chemogenetic activation of AgRP neurons, as well as optogenetic control of AgRP neurons to facilitate acute temporal control not permitted with chemogenetics. A CIF response at test was only observed when mice were fasted during context training and AgRP population activity at test showed an attenuated inhibitory response to food, suggesting increased food-seeking and/or decreased satiety signalling drives the increased feeding response at test. Intriguingly, chemogenetic activation of AgRP neurons during context training did not increase CIF, suggesting precise temporal firing properties may be required. Indeed, termination of AgRP neuronal photostimulation during context training (ON-OFF in context), in the presence or absence of food, increased CIF. Moreover, photoinhibition of AgRP neurons during context training in fasted mice was sufficient to drive a subsequent CIF in the absence of food. Our results suggest that AgRP neurons regulate the acquisition of CIF when the acute inhibition of AgRP activity is temporally matched to context exposure. These results establish acute AgRP inhibition as a salient neural event underscoring the effect of hunger on associative learning.

Identifiants

pubmed: 37690518
pii: S2212-8778(23)00137-0
doi: 10.1016/j.molmet.2023.101803
pmc: PMC10523265
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101803

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier GmbH.. All rights reserved.

Auteurs

Felicia Reed (F)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Alex Reichenbach (A)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Harry Dempsey (H)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Rachel E Clarke (RE)

Department of Neurosciences, Medical University of South Carolina, Charleston, SC, 29425, USA.

Mathieu Mequinion (M)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Romana Stark (R)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Sasha Rawlinson (S)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Claire J Foldi (CJ)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Sarah H Lockie (SH)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia.

Zane B Andrews (ZB)

Monash Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, 3800, Victoria, Australia. Electronic address: Zane.Andrews@monash.edu.

Classifications MeSH