Mathbio Seminar

Speaker: Jose Zamora (Materials and Biomaterials Science and Engineering Graduate Student)
Title: Stochastic Spatial and Temporal Population-based Model for the Co-emergence of Vascular Patterns.
Abstract: We have developed an on-lattice computational model that explores the relationship and co-emergence of two vascular cell types; endothelial cells (EC) and vascular smooth muscle cells (vSMC). These cell types differentiate from a common vascular progenitor cell (VPC) and have been shown to spatially orient themselves when creating functional 3D blood vessels, while in 2D cell cultures these cells self-arrange into spatially unique 2D patterns, e.g. clusters of ECs surrounded by SMCs. To further understand their co-emergence and micropattern formation we developed a computational model that incorporates both biochemical and physical cues. Our model consists of three differential equations, one for each of the three changing cell types; VPC, EC, and vSMC. Within these equations, we account for proliferation, differentiation, cell death, motility, and stochastic noise. We also include density sensing and paracrine signaling equations as potential influencers to their co-emergence. Our results show that we are able to reproduce the observed experimental micropatterns using different variables combinations. Additionally, when analyzing their phase space, we discovered that a well-defined step function emerged for motility and division; indicating a region where micropatterning will form and a region where one cell type will out preform the other. This was not true for the differentiation variable, thus indicating that differentiation does not play a role in micropattern formation. This trend held true for conditions that did and did not included density sensing and/or paracrine signaling. This model could eventually be useful for predicting the spatio-temporal development of 3D blood vessels from VPC.