Research

Drosophila model system

How the brain sets protein appetite in health and disease.

We study how neural circuits, membrane excitability, and internal metabolic signals work together to maintain protein homeostasis. Using Drosophila as a tractable systems model, we connect single-cell physiology to feeding behavior, nutrient-specific motivation, and disease-relevant metabolic disruption.

  • Circuits Protein hunger and homeostatic state encoding
  • Methods Electrophysiology, imaging, genetics, behavior
  • Direction Obesity, cachexia, and metabolism-linked disease

Scientific motivation

How does the nervous system decide what the body needs?

Animals defend internal targets for fundamental needs such as nutrition, hydration, and sleep. Our work asks how those targets are represented biologically, how they are adjusted by physiology, and how they break down in disease states where appetite and metabolism become uncoupled.

Research themes

Three connected questions drive the lab.

01

Encoding nutrient need

We investigate how protein hunger neurons represent intake setpoints and how cellular excitability stores information about internal nutritional demand.

02

Reprogramming appetite

We dissect neuromodulatory and GPCR signaling pathways that tune membrane potential, reshape nutrient-specific motivation, and recalibrate behavioral output.

03

From homeostasis to disease

We extend homeostatic setpoint biology toward obesity, cancer-associated anorexia, and cachexia to understand how peripheral pathology perturbs brain-body communication.

Featured discovery

A physiological variable can store the protein intake setpoint.

Previous work from Guangyan Wu showed that protein hunger neurons encode intake setpoints in their resting membrane potential, linking a homeostatic target to a single trackable electrophysiological parameter. That result opens a broader framework for studying how motivation is programmed at the level of cells and circuits.

Infographic showing a pathway from ion channels to neural state to behavior, with a quote about making hidden internal needs experimentally visible.