M.S. Thesis of Manolya Eyiyurekli:
A Computational Model of Chemotaxis-based Cell Aggregation

Abstract:
We present a 2D computational model that successfully captures the cell be- haviors that play important roles in cell aggregation. A virtual cell in our model is designed as an independent, discrete unit with a collection of parameters and actions. Each cell is defined by its location, number and position of receptors, chemoattractant emission and response rates, age, life cycle stage, proliferation rate and number of attached cells. All cells are capable of emitting and sensing chemoattractant chemical, moving, attaching to other cells, dividing, aging and dying.

We validate and fine-tune our model by comparing simulated 24-hour aggregation experiments with data derived from in vitro PC12 cell experiments. Quantitative comparisons of the aggregate size distributions from the two experiments are pro- duced using the Earth Mover's Distance (EMD) metric. We compare the two size distributions produced after 24 hours of in vitro cell aggregation and the equivalent computer simulated process. Iteratively modifying the model's parameter values and measuring the difference between the in silico and and in vitro results allow us to determine the optimal values that produce simulated aggregation outcomes closely matched to the PC12 experiments. Simulation results confirm the ability of the model to recreate large-scale aggregation behaviors seen in live cell experiments.

Through simulation studies important factors affecting cell aggregation, such as a cell's proliferation rate, response rate to chemoattractant gradient, length of xi the quiescent stage after cell division and up/down-regulation of chemoattractant emission based on the number of attached cells, are identified.


Last modified on February 27, 2006.