Description:

How do organisms build themselves?

Wednesdays@NICO | 12:00-1:00 PM, May 11, 2016 | Room 160, Jacobs Center, 2001 Sheridan Road, Northwestern University

Madhav Mani, Assistant Professor of Engineering Sciences and Applied Mathematics, McCormick School of Engineering

Abstract

Addressing, or even precisely stating, this question is beyond science currently. Thus far the most successful approach to understanding how growth, differentiation, and morphogenesis -- the 3 pillars of development -- are coordinated in a developing organism has been a genetic one. After a historical review of the landmark discoveries of developmental genetics, I will give an overview of research in my own lab that employs tools common to physics. These tools are used to develop phenomenological, but quantitative, descriptions of the dynamics of development -- attempting to capture how development occurs, rather than why. In particular, I will present work on cell mechanics and gene regulation in the context of the developing fly embryo done in collaboration with experimental collaborators (Gregor Lab @ Princeton & Lecuit Lab @ Marseilles).

Bio

This is an exciting time to be studying organismal development. In spite of the progress in molecular biology built up over the last 3 decades, we are still searching for the mechanisms that couple the chemical and physical forms of organism. A misshaped hand, even with the right proportions of different cell types, wouldn't be of much use in gripping a cup of coffee. What are the collective cellular and tissue level mechanisms that generate the complex multicellular patterns of cellular differentiation and morphology in organisms? Recent advance in live fluorescent imaging provide us with a dynamic and spatially resolved view of organismal development, and what is needed now is the development of mathematical tools and models that can help ushering in a new, and physical, understanding of organismal biology. Complementing our interests in developmental biology is our study of gene regulation. In particular, we focus on stochastic and biophysical aspects of gene expression dynamics within the context of developmental systems.

In close collaboration with experimental labs around the world, my group develops quantitative image-analysis tools and mathematical models that guide the construction of inverse modeling schemes to make new and better measurements of live imaging data. When required, forward mathematical models are constructed to make sense of emergent phenomena, and more importantly, to generate predictions and hypotheses that guide future experimentation.