Biophysical Society Thematic Meeting| Les Houches 2019

Multiscale Modeling of Chromatin: Bridging Experiment with Theory

Poster Abstracts


MACROGENOMIC ENGINEERING APPLICATIONS Ranya Virk 1 ; Kai Huang 1 ; Igal Szleifer 1 ; Vadim Backman 1 ;

1 Northwestern University, Biomedical Engineering, Evanston, Illinois, United States An emerging focus in cancer research is the effects of global chromatin organization on the regulation of transcriptional processes on a global scale. Using a combination of nanoimaging devices developed in Professor Backman’s lab to measure chromatin organization, we have already determined that chromatin organization is more heterogeneous in malignant, chemoevasive cancer cells, which corresponds with an increase in transcriptional heterogeneity observed with single-cell RNA sequencing. We have also discovered adjuvant therapies, that reduce heterogeneity in chromatin organization and allow chemotherapies to be more efficacious by reducing transcriptional plasticity of cancer cells. However, we have not yet determined the principal biological, and physico-chemical interactions behind the control of chromatin organization. In order to understand the effect of altering the physico-chemical chromatin nanoenvironment on global chromatin organization we are developing a computational polymer model that realistically represents chromatin structure down to small ~nm length-scales. Potential polymer models include basic homopolymers under confinement such as the fractal globule and tension globule, models that represent biological mechanisms of chromatin organization such as block copolymers to represent A/B compartmentalization, Strings & Binders and loop extrusion to represent looping, and adding torsional stress to induce supercoiling, as well as the de novo self-returning random walk (SRRW) numerical model of chromatin recently developed in Professor Szleifer’s lab. We compare experimentally observed biological properties of chromatin, general rules of polymer physics, and statistical properties of these different polymer models such as contact probability, mass scaling, and mass density distribution to determine which model or combination of models most accurately represents the chromatin polymer.


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