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.
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.
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