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Network dynamics of hypothalamic feeding neurons.

Patrick Sweeney1, Can Chen2,3, Indika Rajapakse4,5

  • 1Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109.

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|April 2, 2021
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Melanocortin 4 receptor (MC4R) neurons in the hypothalamus show dynamic activity changes with fasting and feeding. Distinct neuronal groups encode energy states, revealing insights into hunger and obesity regulation.

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Area of Science:

  • Neuroscience
  • Endocrinology
  • Obesity Research

Background:

  • Mutations in the melanocortin 4 receptor (MC4R) are a leading cause of monogenic obesity.
  • MC4R in the paraventricular nucleus (PVN) of the hypothalamus is crucial for controlling feeding behavior.
  • The in vivo neuronal activity and network dynamics of PVN MC4R neurons remain largely uncharacterized.

Purpose of the Study:

  • To investigate the in vivo activity and network dynamics of PVN MC4R neurons.
  • To determine how energy states (fasting, refeeding) and pharmacological agents affect PVN MC4R neuron activity.
  • To elucidate the neural mechanisms underlying hunger and energy balance regulation.

Main Methods:

  • Utilized in vivo single-cell endomicroscopy to record neuronal activity.
  • Employed mathematical approaches to analyze network dynamics.
  • Administered pharmacological agents, including setmelanotide (MC4R agonist) and MC3R agonists, to assess receptor function.

Main Results:

  • PVN MC4R neurons exhibited significant quantitative and qualitative changes in activity during fasting and refeeding.
  • Pharmacological stimulation of MC4R with setmelanotide increased PVN MC4R neuron activity.
  • MC3R stimulation inhibited PVN MC4R neuron activity, and distinct neuronal ensembles were identified for energy deficit and surfeit states, with enhanced network connectivity during energy surfeit.

Conclusions:

  • PVN MC4R neurons display dynamic activity patterns reflecting energy status.
  • MC4R and MC3R signaling differentially modulate PVN MC4R neuron activity.
  • Specific PVN MC4R neuronal ensembles and their network dynamics are critical for encoding energy balance, offering insights into obesity pathogenesis.