# Investigating Endocytic Mechanisms in Lysosome Rich Enterocytes

> **NIH NIH R01** · DUKE UNIVERSITY · 2024 · $555,595

## Abstract

ABSTRACT
Nutrient absorption in the neonatal mammalian gut relies on intracellular digestion by a population of enterocytes
known as vacuolated or neonatal enterocytes. Recently, we showed these cells are conserved between
zebrafish and mammals and are specialized in the uptake and digestion of dietary proteins. As these cells
possess a prominent lysosomal vacuole and are present in non-mammalian vertebrates such as fish, we refer
to them as Lysosome Rich Enterocytes (LREs). In our previous studies, we found that protein uptake in zebrafish
and mouse LREs is mediated by a scavenger receptor complex composed of cubilin (Cubn), its transmembrane
partner amnionless (Amn), and the endocytic adaptor Dab2. However, the cellular mechanisms that allow LREs
to internalize cargo from the intestinal lumen at an astounding rate are unknown. Here, we will leverage the
experimental advantages of the zebrafish system and the conserved biology of LREs to investigate the endocytic
machinery that allows these cells to support dietary protein absorption in the intestine. Specifically, we will
elucidate the mechanisms regulating a specialized form of clathrin mediated endocytosis that confers LREs a
high capacity for luminal protein uptake.

## Key facts

- **NIH application ID:** 10992834
- **Project number:** 1R01DK137812-01A1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Michel Bagnat
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $555,595
- **Award type:** 1
- **Project period:** 2024-08-01 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10992834

## Citation

> US National Institutes of Health, RePORTER application 10992834, Investigating Endocytic Mechanisms in Lysosome Rich Enterocytes (1R01DK137812-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10992834. Licensed CC0.

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