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R35NIH · NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESNIH

Understanding and controlling collective cell behaviors

Cohen, Daniel (Contact)·PRINCETON UNIVERSITY, NJ·2019–2029·ACTIVE
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INSTITUTION

PRINCETON UNIVERSITY, NJ

PRINCIPAL INVESTIGATOR

Cohen, Daniel (Contact)

FUNDING

$426K

YEAR

2019

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Abstract

Project Summary Our broad goal is to control the collective behavior of cells, similar to how a shepherd and sheepdogs control a flock of sheep. This is of biomedical value because it is the coordinated behaviors of cells that ultimately underlie our ability to heal and regenerate, the assembly of complex organs, and the spread of invasive disease. Given the importance of collective cell behaviors, we propose a two-part research program focused on much more deeply understanding the origins and dynamics of collective cell behaviors, and using this understanding to build new tools to literally ‘herd’ collective cell behaviors. In Program 1, we will investigate the ‘rules’ of collective cell behaviors in much larger tissues than are normally studied (we work at the cm-scale rather than micron-scale). We will connect our prior discoveries on how large tissues coordinate their motion and cell division as they grow and heal to new work on how thousands of cells in a tissue coordinate their use of energy and patterns of gene expression. In Program 2, we will focus on further developing our unique bioelectric tools that tap into an ancient collection of cellular responses to electric currents that we have previously used to control cell migration. Here, we will investigate how electrical cues can regulate collective processes such as tissue shape, stem cell differentiation, and gene activation in engineered tissues. Progress in these areas may help us accelerate injury healing, delay invasive disease, and improve how we grow tissues for regenerative medicine.

R35NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESMaximizing Investigators' Research Award - D Study Section[MRAD]divisionunderstandingstudiedfurtherdelayprocessesresponsesassemblysimilarmotionshapeultimatelysummarysfddifferentiationdiseasecomplexpatternspreviouslyinvasiveflock

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