Statistical physics models for the regulation of the structure of chromatin

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My research program applies methods of computational physics to address the question of how physical constraints lead to complex spatial organization in a cell. It is focused on developing data driven models that draw from strong collaborations with experimental biologists. An important physical process in cell biology is the packaging of DNA into the small volume of the cell. DNA is meticulously arranged; the structure of which affects a host of cellular functions. I have two research efforts that address timely unanswered questions about this process. In collaboration with Olivier Cuvier, a chromatin biologist at CNRS Toulouse, we are working on the development of a predictive mechanistic model for how the structuring of DNA in a cell regulates the genetic information that can get read out. In eukaryotic cells, DNA is packaged into a structure known as chromatin. It is a highly looped structure due to interactions between proteins that are bound to the DNA. The appropriate formation of loops determines whether a gene gets turned on or not. Analyzing data from the Cuvier lab, my group was able to uncover a complex network of interactions between proteins known as insulators which regulate DNA looping and gene expression. Using recently developed experimental techniques, the Cuvier lab will map out which parts of the genome are physically in contact, and how mutations to the insulator network can alter the map. My group will fit this data to a statistical physics model to determine the specific contact energies, leading to the development of a polymer based model for how insulators regulate chromatin structure. With a better understanding of the mechanistic processes involved in looping, we hope to be able to make predictions about when and where a gene will be expressed. Our second effort is focused on uncovering simple physical mechanisms that Nature uses to organize its molecular parts within the tiniest of cells, namely bacteria. We have shown that the entropy of the polymer of genomic DNA can drive localization of protein aggregates to the poles. In some bacteria, polar localized proteins interact with and aid the machinery that segregates replicating DNA. This segregation machinery is also dynamically patterned and recent in vitro measurements have given some insight into its mechanism. However, how the both interacting systems pattern the cell robustly during the important process of replication is not well understood. By modeling the coupled system, our hope is to be able to uncover the design principles of these biomolecular machines. The program of research just described will provide trainees with a diverse skill set. Past trainees have pursued careers in computational biology from academia to the industrial research setting. Such researchers are in high demand in Canada's growing biotech sector.