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Optogenetic Tuning Reveals Rho Amplification-Dependent Dynamics of a Cell Contraction Signal Network

Kamps, Dominic, Koch, Johannes, Juma, Victor O., Campillo-Funollet, Eduard, Graessl, Melanie, Banerjee, Soumya, Mazel, Tomáš, Chen, Xi, Wu, Yao-Wen, Portet, Stephanie, and others. (2020) Optogenetic Tuning Reveals Rho Amplification-Dependent Dynamics of a Cell Contraction Signal Network. Cell Reports, 33 (9). Article Number 108467. ISSN 2211-1247. (doi:10.1016/j.celrep.2020.108467) (KAR id:90467)

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https://doi.org/10.1016/j.celrep.2020.108467

Abstract

Local cell contraction pulses play important roles in tissue and cell morphogenesis. Here, we improve a chemo-optogenetic approach and apply it to investigate the signal network that generates these pulses. We use these measurements to derive and parameterize a system of ordinary differential equations describing temporal signal network dynamics. Bifurcation analysis and numerical simulations predict a strong dependence of oscillatory system dynamics on the concentration of GEF-H1, an Lbc-type RhoGEF, which mediates the positive feedback amplification of Rho activity. This prediction is confirmed experimentally via optogenetic tuning of the effective GEF-H1 concentration in individual living cells. Numerical simulations show that pulse amplitude is most sensitive to external inputs into the myosin component at low GEF-H1 concentrations and that the spatial pulse width is dependent on GEF-H1 diffusion. Our study offers a theoretical framework to explain the emergence of local cell contraction pulses and their modulation by biochemical and mechanical signals.

Item Type: Article
DOI/Identification number: 10.1016/j.celrep.2020.108467
Uncontrolled keywords: rho GTPase; cytoskeleton; mechanotransduction; myosin; cell contraction; optogenetics; parameter inference; reaction-diffusion system; oscillations; dynamical system
Subjects: Q Science > QH Natural history > QH581.2 Cell Biology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Amy Boaler
Date Deposited: 29 Sep 2021 14:16 UTC
Last Modified: 30 Sep 2021 09:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/90467 (The current URI for this page, for reference purposes)
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