# Functional genomics resources for the Drosophila - TR&D3

> **NIH NIH P41** · HARVARD MEDICAL SCHOOL · 2022 · $322,714

## Abstract

PROJECT SUMMARY – TR&D3 
Development of protein technologies for use in vivo in the Drosophila system has lagged behind development 
of molecular genetic technologies. In this project, we will develop protein-based technologies that complement 
and extend the type of studies that can be done in this exemplary model system. We will focus on development 
of proximity labeling, as facilitated by peroxidases or biotin ligases, as tools for in vivo proteomics analysis of 
specific subcellular compartments and signaling. We will additionally develop a robust pipeline for isolation of 
nanobodies that can be used in diverse applications, including for in vivo expression of fusion proteins that 
facilitate visualization and functional blocking. Collaborators with interests in using the technologies to study 
cell biology, development, transcription control, and neuronal networks provide appropriate assays for iterative 
testing and improvement. Altogether, this project will help fill an important gap in the Drosophila toolbox that 
can help provide a more complete picture of functions at the subcellular, cellular, organ, and whole animal 
levels that would not be achievable in cell systems or using only molecular genetic tools.

## Key facts

- **NIH application ID:** 10436795
- **Project number:** 5P41GM132087-04
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** JONATHAN D ZIRIN
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $322,714
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10436795

## Citation

> US National Institutes of Health, RePORTER application 10436795, Functional genomics resources for the Drosophila - TR&D3 (5P41GM132087-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10436795. Licensed CC0.

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