Adhesive dynamics simulation of neutrophil arrest with stochastic activation

随机激活中性粒细胞停滞的粘附动力学模拟

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作者:Ellen F Krasik, Kelly E Caputo, Daniel A Hammer

Abstract

The transition from rolling to firm adhesion is a key step in the adhesion cascade that permits a neutrophil to exit the bloodstream and make its way to a site of inflammation. In this work, we construct an integrated model of neutrophil activation and arrest that combines a biomechanical model of neutrophil adhesion and adhesive dynamics, with fully stochastic signal transduction modeling, in the form of kinetic Monte Carlo simulation within the microvilli. We employ molecular binding parameters gleaned from the literature and from simulation of cell-free rolling mediated by selectin molecules. We create a simplified model of lymphocyte function-associated antigen-1 activation that links P-selectin glycoprotein ligand-1 ligation to integrin activation. The model utilizes an energy profile of various integrin activation states drawn from literature data and permits manipulation of signal diffusivity within the microvillus. Our integrated model recreates neutrophil arrest within physiological timescales, and we demonstrate that increasing signal diffusivity within a microvillus accelerates arrest. If the energy barrier between free unactivated and free activated lymphocyte function-associated antigen-1 increases, the period of rolling before arrest increases. We further demonstrate that, within our model, modification of endothelial ligand surface densities can control arrest. In addition, the relative concentrations of signaling molecules control the fractional activation of the overall signaling pathway and the rolling time to arrest. This work presents the first, to our knowledge, fully stochastic model of neutrophil activation, which, though simplified, can recapitulate significant physiological details of neutrophil arrest yet retains the capacity to incorporate additional information regarding mechanisms of neutrophil signal transduction as they are elucidated.

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