School of Physics Colloquium

Speaker: Sumitabha Brahmachari

Title: Physical modeling of chromosomes across species: mechanistic insights and biological consequences of emergent structural features 

Abstract: Chromosomes are long polymers of DNA that are folded into a tiny nucleus by a concerted activity of various proteins. Quantitative understanding of the mechanistic link between protein activity, chromosome architecture, and biological function is nascent but imperative to comprehend how the DNA code governs cellular life. Establishing these links will steer biological research and yield fruitful discoveries in the physics of active polymers. In this talk, I will focus on a physical simulation framework that incorporates genomic data and furnishes mechanistic insights into regulating chromosome structure. I will discuss how this framework has been crucial in rationalizing our observations, linking the activity of specific proteins to conserved architectural features of chromosomes across species spanning the tree of life. We find that the species-wide diversity of structures emerges from a competition between three kinds of generalized forces, where the balance between these forces depends on the relative abundance of specific proteins and is a predictor of the structure. Using this framework, we further explore the elusive link between chromosome structure and crucial biological functionality like segregation or replicated DNA. The developed framework is an essential stride towards a cohesive, physics-based understanding of the chromosome architecture and its implications for cellular life.

Bio: Sumitabha Brahmachari is a Postdoctoral Associate at the Center for Theoretical Biological Physics at Rice University. He received his Ph.D. from the Department of Physics and Astronomy at Northwestern University, where he was a Molecular Biophysics Training Fellow. During his graduate studies, Dr. Brahmachari developed statistical mechanical models of DNA to understand the interplay of DNA mechanics and topology. He is interested in topics at the interface of physics and biology. He has been working on developing models incorporating statistical mechanics, machine learning, and molecular dynamics techniques to address a range of problems related to chromosome biophysics and genome organization.