Dynamics and pattern formation in differentiating cellular populations

NIH RePORTER · NIH · R01 · $296,359 · view on reporter.nih.gov ↗

Abstract

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.

Key facts

NIH application ID
10906274
Project number
5R01GM144959-04
Recipient
RICE UNIVERSITY
Principal Investigator
Matthew R. Bennett
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$296,359
Award type
5
Project period
2021-09-15 → 2026-08-31