# Patterning dendritic branches with environmental and neuronal surface molecules

> **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $340,040

## Abstract

In this grant, we propose to understand the molecular mechanisms of dendrite
morphogenesis and function. Dendrite morphogenesis determines the connectivity of
neurons. We are using a model cell (PVD in C elegans) to study this question. PVD is a
proprioceptive neuron that senses muscle contraction and regulates animal movement.
In our previous work, we identified the extracellular ligands and their receptor on PVD
that guide the dendrite growth and branching. Here, we propose to understand how the
receptor-ligand interaction triggers signaling mechanisms and leads to cytoskeletal
modifications which eventually drives the morphogenesis events. We will also study how
the neurons regulate receptor signaling using a drug target protein called KPC-1 to
control guidance decisions. We will also understand how the PVD neurons sense
muscle contraction using a putative mechanosensitive channel and how it regulates
neuromuscular activity through a surprising neural circuit feedback mechanism.
Through these experiments, we will gain insights in the molecular logic of dendrite
development. We will identify novel mechanosensitive channels that are important for
body movement regulation.

## Key facts

- **NIH application ID:** 10311468
- **Project number:** 5R01NS082208-08
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** KANG SHEN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $340,040
- **Award type:** 5
- **Project period:** 2013-06-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10311468

## Citation

> US National Institutes of Health, RePORTER application 10311468, Patterning dendritic branches with environmental and neuronal surface molecules (5R01NS082208-08). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10311468. Licensed CC0.

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