# Patterning the Vertebrate Dentition Through Replacement and Repair

> **NIH NIH R01** · GEORGIA INSTITUTE OF TECHNOLOGY · 2020 · $542,742

## Abstract

Project Summary/Abstract
The broad goal of the proposed research is to understand molecular mechanisms of tooth regeneration
and tissue renewal in vertebrates. Our research benefits from explicit integration of experimental systems
(cichlid fishes, zebrafish, mouse) and a unique approach translating new biology from fishes to mammals
and back. In this competitive renewal application, we build on the previous project period to outline three
Specific Aims that fuse unbiased and experimental approaches in multiple vertebrate tooth models to
identify cell populations and molecular signals that direct natural whole-tooth replacement (cichlids and
zebrafish) and mouse incisor tissue renewal. The gaps we aim to fill are significant. One in five humans
presents with a genetic disorder affecting the dentition and nearly 100% develop problems (e.g, cavities)
with age. 30% of people worldwide over the age of 65 lack teeth entirely. Our proposed research will provide
answers to the basic question of how regenerating teeth are partitioned into coordinated zones of renewal
and differentiation, and how mammalian teeth recover from damage. Insights should promote innovative
strategies for bio-inspired regenerative dentistry.

## Key facts

- **NIH application ID:** 9886232
- **Project number:** 5R01DE019637-10
- **Recipient organization:** GEORGIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Jeffery Todd Streelman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $542,742
- **Award type:** 5
- **Project period:** 2010-03-15 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9886232

## Citation

> US National Institutes of Health, RePORTER application 9886232, Patterning the Vertebrate Dentition Through Replacement and Repair (5R01DE019637-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9886232. Licensed CC0.

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