Highly regenerative organisms can respond to injury by initiating developmental programs that replace missing organs rather than creating scar tissue. The task requires flexible cells like stem cells that can re-specify missing tissues but it also requires a signaling system that can organize complex tissue, as is done in embryogenesis. Determining how these robust signaling systems work is one key to understanding how to control regeneration. This proposal develops new techniques that merge technologies - single cell RNA-seq and live confocal imaging of fluorescent proteins - to extend the ability to analyze the dynamic biochemical environment of cells during regeneration. The project uses the highly regenerative plant root as a model, where tools for imaging and classifying cell identity are well developed.
The aims entail the following objectives: 1) Collect single cells from regenerating tissue over a time course to analyze their individual gene expression profile. The technique permits an analysis of the timing and origin of the molecular signatures orchestrate the initial steps of regeneration. 2) Map cellular transcriptomes onto high resolution (confocal) images of regenerating tissue using quantitative analysis techniques specifically developed for the problem. The integration of the two datasets allows the inference of the biochemical environment of a cell in the three dimensional tissue. 3) Map the activity of stem cells onto the high resolution images of regenerating tissue to understand how the injury induced environment communicates to stem cells to initiate the regeneration of specific tissues. One immediate goal is to understand whether cellular transdifferentiation or stem cells direct early events in regeneration. The approach develops new methods that take advantage of the depth of single cell RNA-seq together with the resolution of confocal imaging. The project uses the plant root as a model, but the approach is extendable to many animal models. The overall goal of the project is to determine how highly regenerative organisms respond to injury and reform nearly perfect replacement organs.

Public Health Relevance

The proposal develops methods to integrate new technologies to analyze the complex biochemical state of cells in regenerating tissues. The new approach is designed to learn how highly regenerative organisms activate stem cells in response to injury and will provide new tools for regenerative medicine.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Development - 1 Study Section (DEV1)
Program Officer
Salazar, Desiree Lynn
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
New York University
Schools of Arts and Sciences
New York
United States
Zip Code
Birnbaum, Kenneth D (2018) Power in Numbers: Single-Cell RNA-Seq Strategies to Dissect Complex Tissues. Annu Rev Genet 52:203-221
Ortiz-Ramírez, Carlos; Arevalo, Edgar Demesa; Xu, Xiaosa et al. (2018) An Efficient Cell Sorting Protocol for Maize Protoplasts. Curr Protoc Plant Biol 3:e20072
Birnbaum, Kenneth D; Roudier, François (2017) Epigenetic memory and cell fate reprogramming in plants. Regeneration (Oxf) 4:15-20
Efroni, Idan; Birnbaum, Kenneth D (2016) The potential of single-cell profiling in plants. Genome Biol 17:65
Efroni, Idan; Mello, Alison; Nawy, Tal et al. (2016) Root Regeneration Triggers an Embryo-like Sequence Guided by Hormonal Interactions. Cell 165:1721-1733
Rahni, Ramin; Efroni, Idan; Birnbaum, Kenneth D (2016) A Case for Distributed Control of Local Stem Cell Behavior in Plants. Dev Cell 38:635-42
Efroni, Idan; Ip, Pui-Leng; Nawy, Tal et al. (2015) Quantification of cell identity from single-cell gene expression profiles. Genome Biol 16:9
Para, Alessia; Li, Ying; Marshall-Colón, Amy et al. (2014) Hit-and-run transcriptional control by bZIP1 mediates rapid nutrient signaling in Arabidopsis. Proc Natl Acad Sci U S A 111:10371-6
Bargmann, Bastiaan O R; Vanneste, Steffen; Krouk, Gabriel et al. (2013) A map of cell type-specific auxin responses. Mol Syst Biol 9:688
Bargmann, Bastiaan O R; Marshall-Colon, Amy; Efroni, Idan et al. (2013) TARGET: A Transient Transformation System for Genome-Wide Transcription Factor Target Discovery. Mol Plant 6:978-80

Showing the most recent 10 out of 28 publications