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

  • Dominic Kamps
  • , Johannes Koch
  • , Victor O. Juma
  • , Eduard Campillo-Funollet
  • , Melanie Graessl
  • , Soumya Banerjee
  • , Tomáš Mazel
  • , Xi Chen
  • , Yao Wen Wu
  • , Stephanie Portet
  • , Anotida Madzvamuse
  • , Perihan Nalbant
  • , Leif Dehmelt*
  • *Corresponding author for this work
  • Max Planck Institute of Molecular Physiology
  • TU Dortmund University
  • University of Duisburg-Essen
  • University of Sussex
  • Umeå University
  • University of Manitoba
  • University of Johannesburg
  • University of Bari

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number108467
JournalCell Reports
Volume33
Issue number9
DOIs
StatePublished - 1 Dec 2020

Keywords

  • cell contraction
  • cytoskeleton
  • dynamical system
  • mechanotransduction
  • myosin
  • optogenetics
  • oscillations
  • parameter inference
  • reaction-diffusion system
  • rho GTPase

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