Bayesian Parameter Estimation and Model Selection for Biophysical Models of Leukocyte Rolling
Leukocytes leave the bloodstream and enter into tissue by undergoing the leukocyte adhesion cascade. The endothelium, which covers the inner vessel surface, regulates this process by expressing different adhesion molecules or chemoattractants. This study focuses on the initial interaction between leukocytes and endothelium - the so called selectin dependent leukocyte rolling. Bindings between selectins on the endothelium and their counter ligands on leukocytes are able to slow down the cell to a small fraction of the velocity of the convective blood stream. Interestingly, the rolling process shows a characteristic stop-and-go pattern. We hypothesize that this pattern is caused by binding, unbinding and stretching behavior of microvilli and attached selectin-bindings. In addition, we claim that the analysis of the cell paths allows extracting biophysical parameters of the selectin-cell-interaction. Therefore, we have applied an in vitro flow chamber assay to measure monocytic like THP-1 cell rolling on isolated E-selectin under defined flow conditions. The positions of cells are obtained from sequences of phase contrast images applying self-written image processing software. In addition, we constructed different mathematical models of rolling leukocytes differing in the (visco-)elastic behavior of the simulated selectin-bonds. Bayesian data analysis is applied to estimate the parameters of the mathematical models. Bayesian model selection shows that a viscoelastic model gives the best description of the observed data. Thus, we could identify single molecule events causing the typical stop-and-go pattern of leukocyte rolling. As a byproduct the algorithm permits to directly estimate biomechanical parameters of the nano-scale from microscopic analysis of whole cells.