Bioengineering Seminar Series: Carlos Lopez

Friday, May 6, 2016
9:00 a.m.-10:00 a.m.
Pepco Room (1105), Jeong H. Kim Engineering Building
Dr. Silvina Matysiak
matysiak@umd.edu

Dr. Carlos Lopez
Assistant Professor
Cancer Biology, Vanderbilt-Ingram Cancer Center
Vanderbilt University

Characterization of signal execution modes in intracellular death signaling processes

The key molecular interactions among the Bcl-2 proteins that drive and regulate intracellular Programmed Cell Death  have been identified but their dynamic interactions at the systems level are still poorly understood. Mechanistic models have been formulated to represent cell death decision processes but as more details are included, the models become remarkably complex and therefore difficult to interpret and use to guide further experimentation. Further, experiments to extract information related to key molecular drivers and their dynamic interactions are complicated due to cell-to-cell heterogeneity in PCD execution as well as the fact that most of these interactions take place at the mitochondrial membrane. To overcome this problem, we developed a Python module (TroPyc) within the PySB modeling framework to use algebraic geometry representations of mechanistic models that decompose the dynamic execution of a signaling network into individual contributors. TroPyc is based in max-plus algebra concepts, and allows users to identify the important protein-protein interactions that determine driver species concentration changes in time. We demonstrate the usefulness of TroPyc for the Extrinsic Apoptosis Reaction Model. We calibrate a model, using a Particle-Swarm Optimization to available experimental data and identify the driver species and protein-protein interactions that dictate temporal dynamics and signal execution. We find that there are two dominant modes of signal execution that involve predominantly Bax or Bak, depending on the parameter combinations. Analysis over converged parameter distributions shows significant changes in the model dynamics, indicative of multiple modes of execution that could take place concurrently within a cellular population. The results of this research provide a dynamic perspective for the observed heterogeneous response of cells within a population to perturbations and provide actionable hypotheses for further experimentation.

Audience: Public 

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