(505a) Dynamic Changes in Epigenome Responding to Environmental Chemical Exposure: A Combination of Experimental and Modeling Approach | AIChE

(505a) Dynamic Changes in Epigenome Responding to Environmental Chemical Exposure: A Combination of Experimental and Modeling Approach


Yuan, C., Purdue University
Ramkrishna, D., Purdue University
Epigenetic changes account for dynamic changes in chromatin that persist over time and are inheritable across generations. Significant advances have been made in past years to understand the epigenome, but limited efforts have been focused on modeling epigenome dynamics. Here, we focus on understanding the effects of a pesticide, ATZ [Atrazine: 2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine)] on epigenome and its long-term health implications on central nervous system. Low doses of ATZ exposure has been indicated in Parkinson’s Disease (PD) based on population studies, but the underlying molecular mechanism of action remains elusive. Using SH-SY5Y cells as a model system, we demonstrated dynamic and persistent changes in important epigenetic modifications, i.e., DNA methylation, governing gene regulations harnessing the power of immuno-fluorescent staining and live cell tracking. The collective data serves as the foundation to build a mathematical model to investigate the dynamics of epigenome changes in single cell and population. Our model assumptions are (1) methylation occurs in the presence of methyl donor molecules and an enzyme catalyze the methylation behavior; (2) given that a part of the DNA is methylated, the cells senses the need to provide a process of demethylation toward homeostasis; (3) when sufficient demethylation has occurred, the demethylation enzyme synthesis is turned down. We model the dynamics of methylation by incorporating variables of methylated DNA, demethylated DNA, and their corresponding catalytic enzymes. We use the cybernetic approach [Ramkrishna and Song. Cybernetic Modeling for Bioreaction Engineering. Cambridge University Press, 2018] to represent the regulatory influence on methylation. The cybernetic goal in this context is maximizing survival which is assumed to be accomplished by maximizing the rate of regulation either by methylation or demethylation based on the prevailing methylated fraction. To this extent, we further consider ATZ effect acting as an inhibitor to DNA methylation and determine its effect on epigenome in both short- (acute) and long- (chronic) term. Our model can faithfully capture the dynamic trend exhibited by various epigenetic changes upon external stimuli and offers a powerful tool to connect experimental data with mechanistic understanding for revealing the underlying molecular forces driving epigenome dynamics and predicting new phenotypic state.