Electro-chemo-mechanical model to investigate multi-pulse electric-field-driven integrin clustering
•Cell mechanics and integrin dynamics are coupled in a computational model.•Kinetic Monte Carlo simulation integrates time-dependent electrophoretic diffusion.•Experimental data is incorporated for clinically-relevant electric field therapies.•Multi-pulsed electric fields alter spatio-temporal integ...
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Published in | Bioelectrochemistry (Amsterdam, Netherlands) Vol. 137; p. 107638 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.02.2021
Elsevier BV |
Subjects | |
Online Access | Get full text |
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Summary: | •Cell mechanics and integrin dynamics are coupled in a computational model.•Kinetic Monte Carlo simulation integrates time-dependent electrophoretic diffusion.•Experimental data is incorporated for clinically-relevant electric field therapies.•Multi-pulsed electric fields alter spatio-temporal integrin dynamics.•Membrane stiffness and ligand density mediate electric field induced protein clusters.
The effect of pulsed electric fields (PEFs) on transmembrane proteins is not fully understood; how do chemo-mechanical cues in the microenvironment mediate the electric field sensing by these proteins? To answer this key gap in knowledge, we have developed a kinetic Monte Carlo statistical model of the integrin proteins that integrates three components of the morphogenetic field (i.e., chemical, mechanical, and electrical cues). Specifically, the model incorporates the mechanical stiffness of the cell membrane, the ligand density of the extracellular environment, the glycocalyx stiffness, thermal Brownian motion, and electric field induced diffusion. The effects of both steady-state electric fields and transient PEF pulse trains on integrin clustering are studied. Our results reveal that electric-field-driven integrin clustering is mediated by membrane stiffness and ligand density. In addition, we explore the effects of PEF pulse-train parameters (amplitude, polarity, and pulse-width) on integrin clustering. In summary, we demonstrate a computational methodology to incorporate experimental data and simulate integrin clustering when exposed to PEFs for time-scales comparable to experiments (seconds-minutes). Thus, we propose a blueprint for understanding PEF/electric field effects on protein induced signaling and highlight key impediments to incorporating experimental values into computational models such as the kinetic Monte Carlo method. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1567-5394 1878-562X |
DOI: | 10.1016/j.bioelechem.2020.107638 |