A Computational Model of Chemotaxis-Based Cell Aggregation David Breen Manolya Eyiyurekli Department of Computer Science Peter Lelkes School of Biomedical Engineering, Science    and Health Systems Drexel University 11/17/2018

Chemotaxis The characteristic movement or orientation of an organism or cell along a chemical concentration gradient, either toward or away from the chemical stimulus. 11/17/2018

Motivation Explore and characterize, via simulation, the biological properties and processes that affect chemotaxis-based cell aggregation Provide important knowledge for tissue engineering Cell-cell aggregation reflects “fundamental” biological processes occurring during tissue assembly in vivo Modeling cell aggregates and their assembly/differentiation into functional tissues has implications for the mechanistic understanding of “in vitro embryology” Once processes are understood, we can direct them to control and optimize cell aggregation for tissue engineering 11/17/2018

Approach to Simulation “Simulation is not reality. It simply provides us with the consequences of our assumptions.” Alan Barr, California Institute of Technology “Everything should be made as simple as possible, but no simpler.” Albert Einstein 11/17/2018

Technical Goals Define an accurate computational model that consists of the “essential” components of chemotaxis-based cell aggregation Determine appropriate simplifications and approximations Develop efficient and effective algorithms within a robust, extensible simulation environment Utilize model/environment to computationally investigate cell aggregation behavior 11/17/2018

Cell Model Atomic unit represented by a disk in the plane Diffuses chemoattractant chemical into a 2D environment Detects overall chemical gradient in environment Moves in direction of the gradient Attaches to other cells on contact Divides Ages and eventually dies if unattached 11/17/2018

Cell Computational Cycle 11/17/2018

Algorithmic Optimizations/Features Cells live on a hexagonal grid Environment has toroidal topology Cells may attach to each other at six distinct sites Chemical diffusion approximated by a 1/r concentration field Assume chemical interaction stops beyond a certain distance Chemical concentration stored in the grid for visualization 11/17/2018

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Parametric Studies Perform simulation over a range of parameter values and gather statistics Proliferation & apoptosis rates Chemoattractant diffusion rate Upregulation factors Cell velocity Attachment/detachment probabilities 11/17/2018

Model Fine-Tuning and Verification Perform a “24-hour” simulation Simulation initial conditions taken from experimental data Number of cells, aggregate distribution Compare simulation final results with experimental data Currently fine-tuning model parameters to recreate experimental data 11/17/2018

Comparison with Experimental Data Real Simulated 11/17/2018

Aggregation Data Earth Mover’s Distance used to measure similarity. 11/17/2018

Future Work Complete parameter fine-tuning and model verification Conduct thorough parametric study of model Perform numerous simulations Determine correlation between cell properties and aggregation behavior Extend to 3D Add hydrodynamic forces to simulate bioreactor experiments Augment model to simulate cancer development 11/17/2018