Event

Dr. Bin Zhang 

MIT 

"Genome Organization through Phase Separation: Random yet Precise"

-Abstract: The three-dimensional genome organization plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, DNA replication, etc. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales.  They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications.  In addition, they provided insight into the critical role of the chromatin network in stabilizing multiple liquid droplets.  Applications of these models at a near-atomic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ.

Bio:

Bin Zhang attended the University of Science and Technology of China (USTC) as a chemical physics major. After graduating from USTC in 2007, Bin moved to the United States to pursue doctoral research at the California Institute of Technology in Thomas Miller’s group. Upon graduation, Bin accepted a position as a postdoctoral scholar with Peter G. Wolynes at the Center for Theoretical Biological Physics at Rice University. Bin joined MIT faculty as an assistant professor in 2016. His research focuses on studying three-dimensional genome organization with interdisciplinary approaches that combine bioinformatics analysis, computational modeling and statistical mechanical theory. While at MIT, Bin has received awards that include the Scialog Fellowship and the NSF CAREER Award.

Research

Three-dimensional genome organization plays essential roles for all DNA-templated processes, including gene transcription, gene regulation, DNA replication, etc. Computer simulation can be an effective way of building genome structural models and improving our understanding of these molecular processes. It faces significant challenges, however. First, the human genome consists of over 6 billion base pairs, a system size that exceeds the capacity of traditional simulation approaches, even with the most powerful super-computer. Second, the set of molecular interactions that folds the genome is complex, with a wide array of protein molecules mediating the contacts between DNA segments. This complexity places a high demand on the chemical accuracy of force fields. Finally, the genome is inherently a non-equilibrium system, and one must go beyond conventional sampling techniques to account for the impact ATP-driven molecular motors on its organization. We tackle these challenges by bringing together statistical mechanics, computational modeling, and bioinformatics analysis to invent new methodologies that can accurately model the genome at different lengthscales.

http://zhanggroup.mit.edu

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