# Mapping endogenous protein dynamics in living cells

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $280,502

## Abstract

PROJECT SUMMARY/ABSTRACT
A central challenge of the post-genomic era is to comprehensively characterize the cellular role of the ~20,000
proteins encoded in the human genome. Functional tagging is a powerful strategy to characterize the cellular
role of proteins. In particular, tags allow access to two key features of protein function: localization (using
fluorescent tags) and interaction partners (using epitope tags and immuno-precipitation). Hence, by tagging
proteins in a systematic manner, a comprehensive functional description of an organism’s proteome can be
achieved. For this purpose, we have previously developed FP11 tags based on self-complementing split
fluorescent proteins, which, in combination with gene editing using Cas9/sgRNA ribonucleoprotein (RNPs),
enable rapid, efficient and highly scalable tagging of endogenous proteins in mammalian cell lines. While our
results have paved the way for the large-scale generation of endogenously tagged human cell lines for the
proteome-wide analysis of protein localization and interaction networks in a native cellular context. However,
for practical generation and analysis of large-scale libraries, several major technical limitations still need to be
addressed: brightness, color availability, and live imaging platforms with low photobleaching. In the proposed
project, we plan to engineer improved FP11 tags and new split protein fragment tags to address these technical
challenges. We will also demonstrate the powerful applications by developing a new selective plane
illumination microscopy (SPIM) system to screen an endogenously tagged library.

## Key facts

- **NIH application ID:** 10020992
- **Project number:** 5R01GM131641-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Bo Huang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $280,502
- **Award type:** 5
- **Project period:** 2019-09-20 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10020992

## Citation

> US National Institutes of Health, RePORTER application 10020992, Mapping endogenous protein dynamics in living cells (5R01GM131641-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10020992. Licensed CC0.

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