1. 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

2. Chemotaxis
The characteristic movement or orientation of an organism or cell along a chemical concentration gradient, either toward or away from the chemical stimulus.
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3. 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
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4. 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
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5. 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
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6. 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
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7. Cell Computational Cycle
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8. 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
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9. Cell Aggregation Simulation
Hour 0
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10. Cell Aggregation Simulation
Hour 3
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11. Cell Aggregation Simulation
Hour 6
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12. Cell Aggregation Simulation
Hour 9
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13. Cell Aggregation Simulation
Hour 12
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14. Cell Aggregation Simulation
Hour 15
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15. Cell Aggregation Simulation
Hour 18
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16. Cell Aggregation Simulation
Hour 21
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17. Cell Aggregation Simulation
Hour 25
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18. 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
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19. 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
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20. Comparison with Experimental Data
Real
Simulated
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21. Aggregation Data Earth Mover’s Distance used to measure similarity.
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22. 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