Dynamics and pattern formation in differentiating cellular populations

PROJECT SUMMARY (See instructions):
One hallmark of complex multicellular life is the ability of stem cells to asymmetrically differentiate into
multiple cell types - i.e. the ability for a stem cell to give birth to a new cell type while retaining its own.
The regulation of asymmetric cell division is important for organismal development and processes such as
tissue regeneration and homeostasis. Its improper regulation can lead to aberrant cell growth, abnormal
development (malformation, dysplasia), and tumor formation. From a mathematical modeling perspective,
asymmetric cell division and its regulation are difficult to study because naturally occurring systems are
complex and often only partially understood genetically and molecularly. Experimental studies are also
difficult as it is hard to systematically perturb or tune the regulatory mechanisms governing differentiation.
To address the above issues, the Pis propose to use a synthetic biology approach to develop
mathematical modeling techniques that describe the spatiotemporal dynamics of cells undergoing
asymmetric cell division. In previous work, the Pis have developed a completely controllable synthetic
gene circuit that enables asymmetric cell division in E.coli. This system, though placed in a single celled
organism, can further be augmented to include other hallmarks of multicellular organisms such as cell-cell
signaling, cell motility, cell-cell adhesion, and growth rate regulation. By modularly combining synthetic
asymmetric cell division with these other phenomena, the Pis will have the ability to controllably alter and
fine-tune the regulatory mechanisms governing phenotypic differentiation. The Pis will then formulate
mathematical modeling techniques that span multiple length scales, from the small-scale molecular
mechanisms underlying the genetic regulatory pathways, to the large-scale physical forces that impact the
overall spatiotemporal patterning of the colonies. Overall, this research will lead to better mathematical
models of complex, differentiating multicellular systems.

Grant Number: 5R01GM144959-04
NIH Institute/Center: NIH
Principal Investigator: Matthew Bennett